Publications

2025

Structural equation models for multivariate extremes

M. Krali / A. C. Davison; V. Panaretos (Dir.)  

Lausanne, EPFL, 2025. 

2024

Anthony C. Davison and Raphael de Fondeville’s contribution to the Discussion of ‘Inference for extreme spatial temperature events in a changing climate with application to Ireland’ by Healy et al.

A. C. Davison; R. de Fondeville 

JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES C-APPLIED STATISTICS. 2024. Vol. 74, num. 2. DOI : 10.1093/jrsssc/qlae081.

BAYESIAN MODELING OF INSURANCE CLAIMS FOR HAIL DAMAGE

O. Miralles; A. C. Davison 

Annals of Applied Statistics. 2024. Vol. 18, num. 4, p. 3091 – 3108. DOI : 10.1214/24-AOAS1925.

Correlation of powers of Hüsler-Reiss vectors and Brown-Resnick fields, and application to insured wind losses

E. Koch 

Extremes. 2024. DOI : 10.1007/s10687-023-00474-w.

Anthony C Davison and Igor Rodionov’s contribution to the Discussion of ‘Estimating means of bounded random variables by betting’ by Waudby-Smith and Ramdas

A. C. Davison; I. Rodionov 

Journal Of The Royal Statistical Society Series B-Statistical Methodology. 2024. Vol. 86, num. 1. DOI : 10.1093/jrsssb/qkad118.

Flexible Statistical Inference for Multivariate Extremes

S. Alouini / A. Davison; V. Panaretos (Dir.)  

Lausanne, EPFL, 2024. 

Space-Time Extremes of Severe U.S. Thunderstorm Environments

J. Koh; E. Koch; A. C. Davison 

Journal of the American Statistical Association. 2024. DOI : 10.1080/01621459.2024.2421582.

2023

Valerie Chavez-Demoulin, Anthony C Davison and Erwan Koch’s contribution to the Discussion of ‘The First Discussion Meeting on Statistical aspects of climate change’

V. Chavez-Demoulin; A. C. Davison; E. Koch 

Journal Of The Royal Statistical Society Series A-Statistics In Society. 2023. Vol. 72, num. 4, p. 856 – 857. DOI : 10.1093/jrsssc/qlad051.

Valerie Chavez-Demoulin, Anthony C Davison and Erwan Koch’s contribution to the Discussion of ‘The First Discussion Meeting on Statistical aspects of climate change’

V. Chavez-Demoulin; A. C. Davison; E. Koch 

Journal Of The Royal Statistical Society Series C-Applied Statistics. 2023. Vol. 72, num. 4, p. 856 – 857. DOI : 10.1093/jrsssc/qlad051.

Improved inference for a boundary parameter

S. Elkantassi; R. Bellio; A. R. Brazzale; A. C. Davison 

Canadian Journal Of Statistics-Revue Canadienne De Statistique. 2023. DOI : 10.1002/cjs.11791.

Timing and spatial selection bias in rapid extreme event attribution

O. Miralles; A. C. Davison 

Weather And Climate Extremes. 2023. Vol. 41, p. 100584. DOI : 10.1016/j.wace.2023.100584.

Plant sterols and cholesterol metabolism are associated with five-year cognitive decline in the elderly population

C. Clark; M. Gholam; L. Zullo; A. Kerksiek; E. Castelao et al. 

Iscience. 2023. Vol. 26, num. 6, p. 106740. DOI : 10.1016/j.isci.2023.106740.

Some Reminiscences of David Cox

A. C. Davison 

HARVARD DATA SCIENCE REVIEW. 2023. num. 2. DOI : 10.1162/99608f92.85038493.

Gradient boosting with extreme-value theory for wildfire prediction

J. Koh 

Extremes. 2023. DOI : 10.1007/s10687-022-00454-6.

Higher Order Asymptotics: Applications to Satellite Conjunction and Boundary Problems

S. Elkantassi / A. C. Davison (Dir.)  

Lausanne, EPFL, 2023. 

Spatiotemporal wildfire modeling through point processes with moderate and extreme marks

J. Koh; F. Pimont; J-L. Dupuy; T. Opitz 

The Annals of Applied Statistics. 2023. Vol. 17, num. 1, p. 560 – 582. DOI : 10.1214/22-AOAS1642.

Wind, Hail, and Climate Extremes: Modelling and Attribution Studies for Environmental Data

O. M. A. Miralles / A. C. Davison; V. Panaretos (Dir.)  

Lausanne, EPFL, 2023. 

2022

Causal modelling of heavy-tailed variables and confounders with application to river flow

O. C. Pasche; V. Chavez-Demoulin; A. C. Davison 

Extremes. 2022. DOI : 10.1007/s10687-022-00456-4.

A note on universal inference

T. Tse; A. C. Davison 

Stat. 2022. Vol. 11, num. 1, p. e501. DOI : 10.1002/sta4.501.

Downscaling of Historical Wind Fields over Switzerland Using Generative Adversarial Networks

O. M. A. Miralles; D. Steinfeld; O. Martius; A. Davison 

Artificial Intelligence for the Earth Systems. 2022. Vol. 1, num. 4, p. e220018. DOI : 10.1175/AIES-D-22-0018.1.

Space Oddity? A Statistical Formulation of Conjunction Assessment

S. Elkantassi; A. C. Davison 

Journal Of Guidance Control And Dynamics. 2022. DOI : 10.2514/1.G006282.

Stochastic derivative estimation for max-stable random fields

E. Koch; C. Y. Robert 

European Journal Of Operational Research. 2022. Vol. 302, num. 2, p. 575 – 588. DOI : 10.1016/j.ejor.2021.12.026.

Improved Inference On Risk Measures For Univariate Extremes

L. R. Belzile; A. C. Davison 

Annals Of Applied Statistics. 2022. Vol. 16, num. 3, p. 1524 – 1549. DOI : 10.1214/21-AOAS1555.

Tail Risk Inference via Expectiles in Heavy-Tailed Time Series

A. C. Davison; S. A. Padoan; G. Stupfler 

Journal Of Business & Economic Statistics. 2022. DOI : 10.1080/07350015.2022.2078332.

Functional peaks-over-threshold analysis

R. de Fondeville; A. C. Davison 

Journal Of The Royal Statistical Society Series B-Statistical Methodology. 2022. DOI : 10.1111/rssb.12498.

Influence of advanced footwear technology on sub-2 hour marathon and other top running performances

A. Arderiu; R. de Fondeville 

Journal Of Quantitative Analysis In Sports. 2022. Vol. 18, num. 1, p. 73 – 86. DOI : 10.1515/jqas-2021-0043.

Is There a Cap on Longevity? A Statistical Review

L. R. Belzile; A. C. Davison; J. Gampe; H. Rootzen; D. Zholud 

Annual Review Of Statistics And Its Application. 2022. Vol. 9, p. 21 – 45. DOI : 10.1146/annurev-statistics-040120-025426.

Spatiotemporal modelling of extreme wildfires and severe thunderstorm environments

J. Koh Boon Han / A. C. Davison (Dir.)  

Lausanne, EPFL, 2022. 

Ecological momentary assessment of emotional processing: An exploratory analysis comparing daily life and a psychotherapy analogue session

H. Beuchat; L. Grandjean; J-N. Despland; A. Pascual-Leone; M. Gholam et al. 

Counselling & Psychotherapy Research. 2022. Vol. 22, num. 2, p. 345 – 356. DOI : 10.1002/capr.12455.

2021

Wildlife trafficking via social media in Brazil

T. Wyatt; F. Massé; R. Lima; D. Giovanini; T. Vargas da Costa et al. 

Biological Conservation. 2021. Vol. 265, p. 109420. DOI : 10.1016/j.biocon.2021.109420.

Study protocol for the ETMED-L project: longitudinal study of mental health and interpersonal competence of medical students in a Swiss university using a comprehensive framework of empathy

A. Berney; V. Carrard; S. Berney; K. Schlegel; J. Gaume et al. 

Bmj Open. 2021. Vol. 11, num. 12, p. e053070. DOI : 10.1136/bmjopen-2021-053070.

Human mortality at extreme age

L. R. Belzile; A. C. Davison; H. Rootzen; D. Zholud 

Royal Society Open Science. 2021. Vol. 8, num. 9, p. 202097. DOI : 10.1098/rsos.202097.

Sub‐asymptotic motivation for new conditional multivariate extreme models

T. Lugrin; J. A. Tawn; A. Davison 

Stat. 2021. Vol. 10, num. 1, p. e401. DOI : 10.1002/sta4.401.

Predicting involuntary hospitalization in psychiatry: A machine learning investigation

B. Silva; M. Gholam; P. Golay; C. Bonsack; S. Morandi 

European Psychiatry. 2021. Vol. 64, num. 1, p. e48. DOI : 10.1192/j.eurpsy.2021.2220.

Trends in the Extremes of Environments Associated with Severe US Thunderstorms

E. Koch; J. Koh; A. C. Davison; C. Lepore; M. K. Tippett 

Journal Of Climate. 2021. Vol. 34, num. 4, p. 1259 – 1272. DOI : 10.1175/JCLI-D-19-0826.1.

Practical issues with modeling extreme Brazilian rainfall

P. V. C. Pereira; I. T. S. Previdelli; A. C. Davison 

Brazilian Journal Of Probability And Statistics. 2021. Vol. 35, num. 1, p. 21 – 36. DOI : 10.1214/20-BJPS495.

Multivariate extremes over a random number of observations

E. Hashorva; S. A. Padoan; S. Rizzelli 

Scandinavian Journal Of Statistics. 2021. Vol. 48, num. 3, p. 845 – 880. DOI : 10.1111/sjos.12463.

Estimating an extreme Bayesian network via scalings

C. Klueppelberg; M. Krali 

Journal Of Multivariate Analysis. 2021. Vol. 181, p. 104672. DOI : 10.1016/j.jmva.2020.104672.

Max-infinitely divisible models and inference for spatial extremes

R. Huser; T. Opitz; E. Thibaud 

Scandinavian Journal Of Statistics. 2021. Vol. 48, num. 1, p. 321 – 348. DOI : 10.1111/sjos.12491.

Parameter estimation for discretely observed linear birth-and-death processes

A. C. Davison; S. Hautphenne; A. Kraus 

Biometrics. 2021. Vol. 77, p. 186 – 196. DOI : 10.1111/biom.13282.

2020

Special Issue: “Data Science versus Classical Inference: Prediction, Estimation, and Attribution”, honouring Prof. Brad Efron’s International Prize in Statistics in 2019 Discussion

A. C. Davison 

International Statistical Review. 2020. Vol. 88, p. S70 – S72. DOI : 10.1111/insr.12410.

The challenges of impact evaluation: Attempting to measure the effectiveness of community-based disaster risk management

M. Sarabia; A. R. Kägi Trejo; A. Davison; N. M. Banwell; C. Montes et al. 

International Journal of Disaster Risk Reduction. 2020. Vol. 49, p. 101732. DOI : 10.1016/j.ijdrr.2020.101732.

Simultaneous autoregressive models for spatial extremes

M. J. Fix; D. S. Cooley; E. Thibaud 

Environmetrics. 2020.  p. e2656. DOI : 10.1002/env.2656.

An unethical optimization principle

N. Beale; H. Battey; A. C. Davison; R. S. MacKay 

Royal Society Open Science. 2020. Vol. 7, num. 7, p. 200462. DOI : 10.1098/rsos.200462.

A fully joint Bayesian quantitative trait locus mapping of human protein abundance in plasma

H. Ruffieux; J. Carayol; R. Popescu; M-E. Harper; R. Dent et al. 

Plos Computational Biology. 2020. Vol. 16, num. 6, p. e1007882. DOI : 10.1371/journal.pcbi.1007882.

A Global-Local Approach For Detecting Hotspots In Multiple-Response Regression

H. Ruffieux; A. C. Davison; J. Hager; J. Inshaw; B. P. Fairfax et al. 

Annals Of Applied Statistics. 2020. Vol. 14, num. 2, p. 905 – 928. DOI : 10.1214/20-AOAS1332.

Discussion

A. C. Davison 

Journal Of The American Statistical Association. 2020. Vol. 115, num. 530, p. 663 – 664. DOI : 10.1080/01621459.2020.1762616.

Strong convergence of multivariate maxima

M. Falk; S. A. Padoan; S. Rizzelli 

Journal Of Applied Probability. 2020. Vol. 57, num. 1, p. 314 – 331. DOI : 10.1017/jpr.2019.100.

Linking micro and macroevolution in the presence of migration

P. Duchen; S. Hautphenne; L. Lehmann; N. Salamin 

Journal Of Theoretical Biology. 2020. Vol. 486, p. 110087. DOI : 10.1016/j.jtbi.2019.110087.

Inference on the Angular Distribution of Extremes

C. A. Semadeni / A. C. Davison (Dir.)  

Lausanne, EPFL, 2020. 

2019

Exploration and Inference in Spatial Extremes Using Empirical Basis Functions

S. A. Morris; B. J. Reich; E. Thibaud 

Journal Of Agricultural Biological And Environmental Statistics. 2019. Vol. 24, num. 4, p. 555 – 572. DOI : 10.1007/s13253-019-00359-1.

Comment: Models Are Approximations!

A. C. Davison; E. Koch; J. Koh 

Statistical Science. 2019. Vol. 34, num. 4, p. 584 – 590. DOI : 10.1214/19-STS746.

Extinction In Lower Hessenberg Branching Processes With Countably Many Types

P. Braunsteins; S. Hautphenne 

Annals Of Applied Probability. 2019. Vol. 29, num. 5, p. 2782 – 2818. DOI : 10.1214/19-AAP1464.

Decompositions of dependence for high-dimensional extremes

D. Cooley; E. Thibaud 

Biometrika. 2019. Vol. 106, num. 3, p. 587 – 604. DOI : 10.1093/biomet/asz028.

A nonparametric method for producing isolines of bivariate exceedance probabilities

D. Cooley; E. Thibaud; F. Castillo; M. F. Wehner 

Extremes. 2019. Vol. 22, num. 3, p. 373 – 390. DOI : 10.1007/s10687-019-00348-0.

A central limit theorem for functions of stationary max-stable random fields on R-d

E. Koch; C. Dombry; C. Y. Robert 

Stochastic Processes And Their Applications. 2019. Vol. 129, num. 9, p. 3406 – 3430. DOI : 10.1016/j.spa.2018.09.014.

Fitting Markovian binary trees using global and individual demographic data

S. Hautphenne; M. Massaro; K. Turner 

Theoretical Population Biology. 2019. Vol. 128, p. 39 – 50. DOI : 10.1016/j.tpb.2019.04.007.

The time-dependent expected reward and deviation matrix of a finite QBD process

S. Dendievel; S. Hautphenne; G. Latouche; P. G. Taylor 

Linear Algebra And Its Applications. 2019. Vol. 570, p. 61 – 92. DOI : 10.1016/j.laa.2019.02.002.

Spatial Risk Measures and Rate of Spatial Diversification

E. Koch 

Risks. 2019. Vol. 7, num. 2, p. 52. DOI : 10.3390/risks7020052.

A pathwise approach to the extinction of branching processes with countably many types

P. Braunsteins; G. Decrouez; S. Hautphenne 

Stochastic Processes And Their Applications. 2019. Vol. 129, num. 3, p. 713 – 739. DOI : 10.1016/j.spa.2018.03.013.

Extremal behaviour of aggregated data with an application to downscaling

S. Engelke; R. De Fondeville; M. Oesting 

Biometrika. 2019. Vol. 106, num. 1, p. 127 – 144. DOI : 10.1093/biomet/asy052.

Geometric ergodicity for some space-time max-stable Markov chains

E. Koch; C. Y. Robert 

Statistics & Probability Letters. 2019. Vol. 145, p. 43 – 49. DOI : 10.1016/j.spl.2018.06.014.

Genome-wide gene-based analyses of weight loss interventions identify a potential role for NKX6.3 in metabolism

A. Valsesia; Q-P. Wang; N. Gheldof; J. Carayol; H. Ruffieux et al. 

Nature Communications. 2019. Vol. 10, p. 540. DOI : 10.1038/s41467-019-08492-8.

Fast Automatic Smoothing for Generalized Additive Models

Y. El-Bachir; A. C. Davison 

Journal Of Machine Learning Research. 2019. Vol. 20, p. 173.

Automatic L2 Regularization for Multiple Generalized Additive Models

Y. El Bachir / A. C. Davison (Dir.)  

Lausanne, EPFL, 2019. 

Large-scale variational inference for Bayesian joint regression modelling of high-dimensional genetic data

H. Ruffieux / A. C. Davison; J. Hager (Dir.)  

Lausanne, EPFL, 2019. 

Contributions to Likelihood-Based Modelling of Extreme Values

L. Raymond-Belzile / A. C. Davison (Dir.)  

Lausanne, EPFL, 2019. 

2018

Dependence properties of spatial rainfall extremes and areal reduction factors

P. D. Le; A. C. Davison; S. Engelke; M. Leonard; S. Westra 

Journal of Hydrology. 2018. Vol. 565, p. 711 – 719. DOI : 10.1016/j.jhydrol.2018.08.061.

High-dimensional peaks-over-threshold inference

R. de Fondeville; A. C. Davison 

Biometrika. 2018. Vol. 105, num. 3, p. 575 – 592. DOI : 10.1093/biomet/asy026.

‘The life of man, solitary, poore, nasty, brutish, and short’: Discussion of the paper by Rootzen and Zholud

A. C. Davison 

Extremes. 2018. Vol. 21, num. 3, p. 365 – 372. DOI : 10.1007/s10687-018-0329-5.

Functional Peaks-Over-Threshold Analysis for Complex Extreme Events

R. G. T. M. M. de Deloÿe et Fourcade de Fondeville / A. C. Davison (Dir.)  

Lausanne, EPFL, 2018. 

Semiparametric Bayesian Risk Estimation for Complex Extremes

T. Lugrin / A. C. Davison; J. A. Tawn (Dir.)  

Lausanne, EPFL, 2018. 

Optimal regionalization of extreme value distributions for flood estimation

P. Asadi; S. Engelke; A. Davison 

JOURNAL OF HYDROLOGY. 2018. Vol. 556, p. 182 – 193. DOI : 10.1016/j.jhydrol.2017.10.051.

Automatic module selection from several microarray gene expression studies

A. Zollinger; A. Davison; D. Goldstein 

BIOSTATISTICS. 2018. Vol. 19, num. 2, p. 153 – 168. DOI : 10.1093/biostatistics/kxx032.

2017

Efficient inference for genetic association studies with multiple outcomes

H. Ruffieux; A. C. Davison; J. Hager; I. Irincheeva 

Biostatistics. 2017. Vol. 18, num. 4, p. 618 – 636. DOI : 10.1093/biostatistics/kxx007.

Generalized Pickands constants and stationary max-stable processes

K. Debicki; S. Engelke; E. Hashorva 

Extremes. 2017. Vol. 20, num. 3, p. 493 – 517. DOI : 10.1007/s10687-017-0289-1.

Contributions to Modelling Extremes of Spatial Data

L. Frossard / A. C. Davison (Dir.)  

Lausanne, EPFL, 2017. 

A Functional Framework for Enhanced Ultrasound Imaging

L. Roquette 

2017.

Quasi-random numbers for copula models

M. Cambou; M. Hofert; C. Lemieux 

Statistics And Computing. 2017. Vol. 27, num. 5, p. 1307 – 1329. DOI : 10.1007/s11222-016-9688-4.

Extremal attractors of Liouville copulas

L. R. Belzile; J. G. Nešlehová 

Journal of Multivariate Analysis. 2017. Vol. 160, p. 68 – 92. DOI : 10.1016/j.jmva.2017.05.008.

Bridging asymptotic independence and dependence in spatial extremes using Gaussian scale mixtures

R. Huser; T. Opitz; E. Thibaud 

Spatial Statistics. 2017. Vol. 21, p. 166 – 186. DOI : 10.1016/j.spasta.2017.06.004.

Modelling across extremal dependence classes

J. L. Wadsworth; J. A. Tawn; A. C. Davison; D. M. Elton 

Journal Of The Royal Statistical Society Series B-Statistical Methodology. 2017. Vol. 79, num. 1, p. 149 – 175. DOI : 10.1111/rssb.12157.

Robust Bounds In Multivariate Extremes

S. Engelke; J. Ivanovs 

Annals Of Applied Probability. 2017. Vol. 27, num. 6, p. 3706 – 3734. DOI : 10.1214/17-Aap1294.

2016

A characterization of the normal distribution using stationary max-stable processes

S. Engelke; Z. Kabluchko 

Extremes. 2016. Vol. 19, num. 1, p. 1 – 6. DOI : 10.1007/s10687-015-0235-z.

Bayesian uncertainty management in temporal dependence of extremes

T. Lugrin; A. C. Davison; J. A. Tawn 

Extremes. 2016. Vol. 19, num. 3, p. 491 – 515. DOI : 10.1007/s10687-016-0258-0.

Lyapunov Exponents for Branching Processes in a Random Environment: The Effect of Information

S. Hautphenne; G. Latouche 

Journal Of Statistical Physics. 2016. Vol. 163, num. 2, p. 393 – 410. DOI : 10.1007/s10955-016-1474-3.

A Bayesian view of doubly robust causal inference

O. Saarela; L. R. Belzile; D. A. Stephens 

Biometrika. 2016. Vol. 103, num. 3, p. 667 – 681. DOI : 10.1093/biomet/asw025.

ODE parameter estimation through a runner’s model application

L. Roquette 

2016.

Exact simulation of max-stable processes

C. Dombry; S. Engelke; M. Oesting 

Biometrika. 2016. Vol. 103, num. 2, p. 303 – 317. DOI : 10.1093/biomet/asw008.

The roles of coupling and the deviation matrix in determining the value of capacity in M/M/1/C queues

P. Braunsteins; S. Hautphenne; P. G. Taylor 

Queueing Systems. 2016. Vol. 83, num. 1-2, p. 157 – 179. DOI : 10.1007/s11134-016-9480-3.

Bayesian Inference For The Brown-Resnick Process, With An Application To Extreme Low Temperatures

E. Thibaud; J. Aalto; D. S. Cooley; A. C. Davison; J. Heikkinen 

Annals of Applied Statistics. 2016. Vol. 10, num. 4, p. 2303 – 2324. DOI : 10.1214/16-Aoas980.

A Levy-derived process seen from its supremum and max-stable processes

S. Engelke; J. Ivanovs 

Electronic Journal Of Probability. 2016. Vol. 21, p. 14. DOI : 10.1214/16-Ejp1112.

Likelihood estimators for multivariate extremes

R. Huser; A. C. Davison; M. G. Genton 

Extremes. 2016. Vol. 19, num. 1, p. 79 – 103. DOI : 10.1007/s10687-015-0230-4.

2015

Objective Bayesian Model Selection

T. Lugrin 

2015

A simple model-based approach to variable selection in classification and clustering

V. Partovi Nia; A. C. Davison 

Canadian Journal Of Statistics-Revue Canadienne De Statistique. 2015. Vol. 43, num. 2, p. 157 – 175. DOI : 10.1002/cjs.11241.

Meta-analysis of incomplete microarray studies

A. Leboucq; A. C. Davison; D. Goldstein 

Biostatistics. 2015. Vol. 16, num. 4, p. 686 – 700. DOI : 10.1093/biostatistics/kxv014.

Extremal behavior of squared Bessel processes attracted by the Brown-Resnick process

B. Das; S. Engelke; E. K. Hashorva 

Stochastic Processes And Their Applications. 2015. Vol. 125, num. 2, p. 780 – 796. DOI : 10.1016/j.spa.2014.09.006.

Likelihood Estimation for the INAR(p) Model by Saddlepoint Approximation

X. Pedeli; A. C. Davison; K. Fokianos 

Journal Of The American Statistical Association. 2015. Vol. 110, num. 511, p. 1229 – 1238. DOI : 10.1080/01621459.2014.983230.

Max-stable processes and stationary systems of Levy particles

S. Engelke; Z. Kabluchko 

Stochastic Processes And Their Applications. 2015. Vol. 125, num. 11, p. 4272 – 4299. DOI : 10.1016/j.spa.2015.07.001.

Statistics of Extremes

A. C. Davison; R. Huser 

Annual Review Of Statistics And Its Application; Palo Alto: Annual Reviews, 2015. p. 203 – 235.

2014

Spectral Density Ratio Models for Multivariate Extremes

M. De Carvalho; A. C. Davison 

Journal Of The American Statistical Association. 2014. Vol. 109, num. 506, p. 764 – 776. DOI : 10.1080/01621459.2013.872651.

Meta-analysis of Incomplete Microarray Studies

A. Leboucq / A. C. Davison; D. Goldstein (Dir.)  

Lausanne, EPFL, 2014. 

Space-time modelling of extreme events

R. Huser; A. C. Davison 

Journal Of The Royal Statistical Society Series B-Statistical Methodology. 2014. Vol. 76, num. 2, p. 439 – 461. DOI : 10.1111/rssb.12035.

Contributions to Spatial Statistics : Species Distributions and Rare Events

E. Thibaud / A. C. Davison (Dir.)  

Lausanne, EPFL, 2014. 

Measuring the relative effect of factors affecting species distribution model predictions

E. Thibaud; B. Petitpierre; O. Broennimann; A. C. Davison; A. Guisan 

Methods In Ecology And Evolution. 2014. Vol. 5, num. 9, p. 947 – 955. DOI : 10.1111/2041-210X.12203.

Additive Smooth Modelling with Splines

T. Lugrin 

2014

Accurate Directional Inference for Vector Parameters in Linear Exponential Families

A. C. Davison; D. A. S. Fraser; N. Reid; N. Sartori 

Journal Of The American Statistical Association. 2014. Vol. 109, num. 505, p. 302 – 314. DOI : 10.1080/01621459.2013.839451.

Efficient inference for spatial extreme value processes associated to log-Gaussian random functions

J. L. Wadsworth; J. A. Tawn 

Biometrika. 2014. Vol. 101, num. 1, p. 1 – 15. DOI : 10.1093/biomet/ast042.

Heavy-tail Phenomena: Spatio-temporal Extremal Dependence

T. Lugrin 

2014

2013

Nonstationary Positive Definite Tapering On The Plane

E. Anderes; R. Huser; D. Nychka; M. Coram 

Journal Of Computational And Graphical Statistics. 2013. Vol. 22, num. 4, p. 848 – 865. DOI : 10.1080/10618600.2012.729982.

On the relationship between total ozone and atmospheric dynamics and chemistry at mid-latitudes – Part 2: The effects of the El Nino/Southern Oscillation, volcanic eruptions and contributions of atmospheric dynamics and chemistry to long-term total ozone changes

H. E. Rieder; L. Frossard; M. Ribatet; J. Staehelin; J. A. Maeder et al. 

Atmospheric Chemistry And Physics. 2013. Vol. 13, num. 1, p. 165 – 179. DOI : 10.5194/acp-13-165-2013.

A Euclidean Likelihood Estimator for Bivariate Tail Dependence

M. de Carvalho; B. Oumow; J. J. Segers; M. Warchoł 

Communications in Statistics – Theory and Methods. 2013. Vol. 42, num. 7, p. 1176 – 1192. DOI : 10.1080/03610926.2012.709905.

From pointwise testing to a regional vision: An integrated statistical approach to detect nonstationarity in extreme daily rainfall. Application to the Sahelian region

G. Panthou; T. Vischel; T. Lebel; G. Quantin; A-C. F. Pugin et al. 

Journal of Geophysical Research: Atmospheres. 2013. Vol. 118, num. 15, p. 8222 – 8237. DOI : 10.1002/jgrd.50340.

Bayesian Semiparametrics for Modelling the Clustering of Extreme Values

T. Lugrin 

2013.

Statistical Modeling and Inference for Spatio-Temporal Extremes

R. Huser / A. C. Davison (Dir.)  

Lausanne, EPFL, 2013. 

A new representation for multivariate tail probabilities

J. L. Wadsworth; J. A. Tawn 

Bernoulli. 2013. Vol. 19, num. 5B, p. 2689 – 2714. DOI : 10.3150/12-Bej471.

On the relationship between total ozone and atmospheric dynamics and chemistry at mid-latitudes – Part 1: Statistical models and spatial fingerprints of atmospheric dynamics and chemistry

L. Frossard; H. E. Rieder; M. Ribatet; J. Staehelin; J. A. Maeder et al. 

Atmospheric Chemistry And Physics. 2013. Vol. 13, num. 1, p. 147 – 164. DOI : 10.5194/acp-13-147-2013.

Composite likelihood estimation for the Brown–Resnick process

R. Huser; A. C. Davison 

Biometrika. 2013. Vol. 100, num. 2, p. 511 – 518. DOI : 10.1093/biomet/ass089.

Spectral modeling of time series with missing data

P. C. Rodrigues; M. De Carvalho 

Applied Mathematical Modelling. 2013. Vol. 37, num. 7, p. 4676 – 4684. DOI : 10.1016/j.apm.2012.09.040.

Threshold modeling of extreme spatial rainfall

E. Thibaud; R. Mutzner; A. C. Davison 

Water Resources Research. 2013. Vol. 49, num. 8, p. 4633 – 4644. DOI : 10.1002/wrcr.20329.

Geostatistics of Dependent and Asymptotically Independent Extremes

A. C. Davison; R. Huser; E. Thibaud 

Mathematical Geosciences. 2013. Vol. 45, num. 5, p. 511 – 529. DOI : 10.1007/s11004-013-9469-y.

2012

A generalization of the Solis-Wets method

M. de Carvalho 

Journal Of Statistical Planning And Inference. 2012. Vol. 142, p. 633 – 644. DOI : 10.1016/j.jspi.2011.08.016.

Tracking the US business cycle with a singular spectrum analysis

M. de Carvalho; P. C. Rodrigues; A. Rua 

Economics Letters. 2012. Vol. 114, p. 32 – 35. DOI : 10.1016/j.econlet.2011.09.007.

Bivariate Extreme Statistics, Ii

M. de Carvalho; A. Ramos 

Revstat-Statistical Journal. 2012. Vol. 10, p. 83 – 107.

Digging out the PPP hypothesis: an integrated empirical coverage

M. de Carvalho; P. Julio 

Empirical Economics. 2012. Vol. 42, p. 713 – 744. DOI : 10.1007/s00181-010-0441-0.

A dimension reduction technique for estimation in linear mixed models

M. de Carvalho; M. Fonseca; M. Oliveira; J. T. Mexia 

2012. Conference of the LinStat, Tomar, PORTUGAL, Jul 27-31, 2010. p. 219 – 226. DOI : 10.1080/00949655.2011.604032.

High-Dimensional Bayesian Clustering with Variable Selection: The R Package bclust

V. P. Nia; A. C. Davison 

Journal Of Statistical Software. 2012. Vol. 47, p. 1 – 22. DOI : 10.18637/jss.v047.i05.

A case study of a “Dragon-King”: The 1999 Venezuelan catastrophe

M. Sueveges; A. C. Davison 

European Physical Journal-Special Topics. 2012. Vol. 205, p. 131 – 146. DOI : 10.1140/epjst/e2012-01566-6.

Statistical Analysis of Mountain Permafrost Temperatures

E. Zenklusen Mutter / A. C. Davison; M. Phillips (Dir.)  

Lausanne, EPFL, 2012. 

Long-term changes in annual maximum snow depth and snowfall in Switzerland based on extreme value statistics

C. Marty; J. Blanchet 

Climatic Change. 2012. Vol. 111, p. 705 – 721. DOI : 10.1007/s10584-011-0159-9.

Geostatistics of extremes

A. C. Davison; M. M. Gholamrezaee 

Proceedings of the Royal Society of London Series A: Mathematical and Physical Sciences. 2012. Vol. 468, p. 581 – 608. DOI : 10.1098/rspa.2011.0412.

Serum antiglycan antibody detection of nonmucinous ovarian cancers by using a printed glycan array

F. Jacob; D. R. Goldstein; N. V. Bovin; T. Pochechueva; M. Spengler et al. 

International Journal Of Cancer. 2012. Vol. 130, p. 138 – 146. DOI : 10.1002/ijc.26002.

Modelling Time Series Extremes

V. Chavez-Demoulin; A. C. Davison 

Revstat-Statistical Journal. 2012. Vol. 10, p. 109 – 133.

Open Support Platform for Environmental Research (OSPER)-tools for the discovery and exploitation of environmental data

N. Dawes; M. Lehning; M. Bavay; S. Sofiane; I. Iosifescu et al. 

2012. AGU Fall Meeting.

Diabetes imaging — quantitative assessment of islets of Langerhans distribution in murine pancreas using extended-focus optical coherence microscopy

C. Berclaz; J. Goulley; M. Villiger; A. Bouwens; E. Martin-williams et al. 

Biomedical Optics Express. 2012. Vol. 3, num. 6, p. 1365 – . DOI : 10.1364/BOE.3.001365.

Extreme rainfall in West Africa: A regional modeling

G. Panthou; T. Vischel; T. Lebel; J. Blanchet; G. Quantin et al. 

Water Resources Research. 2012. Vol. 48, num. 8, p. W08501. DOI : 10.1029/2012Wr012052.

Anti-glycan antibodies in epithelial ovarian cancer

F. Jacob; D. Goldstein; T. Pochechueva; B. W. C. Tse; N. V. Bovin et al. 

2012.  p. S29 – S29.

Bayesian inference from composite likelihoods, with an application to spatial extremes

M. Ribatet; D. Cooley; A. C. Davison 

Statistica Sinica. 2012. Vol. 22, num. 2, p. 813 – 845. DOI : 10.5705/ss.2009.248.

Extremes: spatial parametric modeling

A. C. Davison 

Encyclopedia of Environmetrics Second Edition; Chichester, UK: John Wiley, 2012. p. 984 – 990.

Statistical Modeling of Spatial Extremes

A. C. Davison; S. A. Padoan; M. Ribatet 

Statistical Science. 2012. Vol. 27, p. 161 – 186. DOI : 10.1214/11-STS376.

Statistical modelling of ground temperature in mountain permafrost

J. Blanchet; A. C. Davison 

Proceedings Of The Royal Society A-Mathematical Physical And Engineering Sciences. 2012. Vol. 468, p. 1472 – 1495. DOI : 10.1098/rspa.2011.0615.

From sensor networks to connected analysis tools

N. Dawes; M. Bavay; T. Egger; S. Sarni; A. Salehi et al. 

2012. European Geosciences Union General Assembly 2012, Vienna, Austria, April 22-27, 2012.

2011

Discussion of the papers by Dankers and Feyen, Cooley, and Keef

A. C. Davison 

2011. International Statistical Institute, Dublin, Ireland, August 21-26, 2011.

Discussion of `Threshold modelling of spatially dependent non-stationary extremes with application to hurricane-induced wave heights’ by P. J. Northrop and P. Jonathan

V. Chavez-Demoulin; A. C. Davison; L. Frossard 

Environmetrics. 2011. Vol. 22, p. 810 – 812. DOI : 10.1002/env.1125.

Extreme temperature analysis under forest cover compared to an open field

J. Ferrez; A. C. Davison; M. Rebetez 

Agricultural And Forest Meteorology. 2011. Vol. 151, p. 992 – 1001. DOI : 10.1016/j.agrformet.2011.03.005.

Hierarchical wavelet modelling of environmental sensor data

Y. Ruffieux; A. C. Davison 

Brazilian Journal of Probability and Statistics. 2011. Vol. 25, p. 406 – 420. DOI : 10.1214/11-BJPS154.

Statistics of extremes

M. Lovric; A. C. Davison 

International Encyclopedia of Statistical Science; new York: Springer, 2011. p. 1484 – .

Spatial modelling of extreme snow depth

J. Blanchet; A. C. Davison 

Annals of Applied Statistics. 2011. Vol. 5, p. 1699 – 1725. DOI : 10.1214/11-AOAS464.

No benefit from combining HE4 and CA125 as ovarian tumor markers in a clinical setting

F. Jacob; M. Meier; R. Caduff; D. Goldstein; T. Pochechueva et al. 

Gynecologic Oncology. 2011. Vol. 121, p. 487 – 491. DOI : 10.1016/j.ygyno.2011.02.022.

Comparison of Models for Olfactometer Data

A. C. Davison; I. Ricard 

Journal of Agricultural, Biological, and Environmental Statistics. 2011. Vol. 16, num. 2, p. 157 – 169. DOI : 10.1007/s13253-010-0042-6.

SpaCEM(3): a software for biological module detection when data is incomplete, high dimensional and dependent

M. Vignes; J. Blanchet; D. Leroux; F. Forbes 

Bioinformatics. 2011. Vol. 27, p. 881 – 882. DOI : 10.1093/bioinformatics/btr034.

Comparison of printed glycan array, suspension array and ELISA in the detection of human anti-glycan antibodies

T. Pochechueva; F. Jacob; D. R. Goldstein; M. E. Huflejt; A. Chinarev et al. 

Glycoconjugate Journal. 2011. Vol. 28, p. 507 – 517. DOI : 10.1007/s10719-011-9349-y.

2010

Likelihood-Based Inference for Max-Stable Processes

S. A. Padoan; M. Ribatet; S. A. Sisson 

Journal of the American Statistical Association. 2010. Vol. 105, num. 489, p. 263 – 277. DOI : 10.1198/jasa.2009.tm08577.

Bayesian modelling for matching and alignment of biomolecules

P. J. Green; K. V. Mardia; V. B. Nyirongo; Y. Ruffieux 

The Oxford Handbook of Applied Bayesian Analysis; Oxford: Oxford University Press, 2010. p. 27 – 50.

Curvature and Strength of Ni-YSZ Solid Oxide Half-cells after RedOx Treatments

A. Faes; H. L. Frandsen; A. Kaiser; D. R. Goldstein; M. Pihlatie 

Journal of Fuel Cells Science and Technology. 2010. Vol. 7, num. 5, p. 051011. DOI : 10.1115/1.4001019.

Effects of Rewarding and Unrewarding Experiences on the Response to Host-induced Plant Odors of the Generalist Parasitoid Cotesia marginiventris (Hymenoptera: Braconidae)

A. Costa; I. Ricard; A. C. Davison; T. C. J. Turlings 

Journal of Insect Behavior. 2010. Vol. 23, num. 4, p. 303 – 318. DOI : 10.1007/s10905-010-9215-y.

The MicroArray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models

L. Shi; G. Campbell; W. D. Jones; F. Campagne; Z. Wen et al. 

Nature Biotechnology. 2010. Vol. 28, p. 827 – U109. DOI : 10.1038/nbt.1665.

Extreme events in total ozone over Arosa—Part 2: Fingerprints of atmospheric dynamics and chemistry and effects on mean values and long-term changes

H. E. Rieder; J. Staehelin; J. A. Maeder; T. Peter; M. Ribatet et al. 

Atmospheric Chemistry And Physics. 2010. Vol. 10, p. 10033 – 10045. DOI : 10.5194/acp-10-10033-2010.

Comparison of Meta-analysis to Combined Analysis of a Replicated Microarray Study

D. R. Goldstein; M. Delorenzi; R. Luthi-Carter; T. Sengstag 

Meta-analysis and Combining Information in Genetics; Chapman&Hall/CRC, 2010. p. 135 – 156.

Relationship between high daily erythemal UV doses, total ozone, surface albedo and cloudiness: An analysis of 30 years of data from Switzerland and Austria

H. E. Rieder; J. Staehelin; P. Weihs; L. Vuilleumier; J. A. Maeder et al. 

Atmospheric Research. 2010. Vol. 98, p. 9 – 20. DOI : 10.1016/j.atmosres.2010.03.006.

Extreme events in total ozone over Arosa—Part 1: Application of extreme value theory

H. E. Rieder; J. Staehelin; J. A. Maeder; T. Peter; M. Ribatet et al. 

Atmospheric Chemistry And Physics. 2010. Vol. 10, p. 10021 – 10031. DOI : 10.5194/acp-10-10021-2010.

Mapping snow depth return levels: smooth spatial modeling versus station interpolation

J. Blanchet; M. Lehning 

Hydrology and Earth System Sciences. 2010. Vol. 14, num. 12, p. 2527 – 2544. DOI : 10.5194/hess-14-2527-2010.

Geostatistics of Extremes : A Composite Likelihood Approach

M. M. Gholam Rezaee / A. C. Davison (Dir.)  

Lausanne, EPFL, 2010. 

Three Examples of Accurate Likelihood Inference

C. Lozada-Can; A. C. Davison 

American Statistician. 2010. Vol. 64, p. 131 – 139. DOI : 10.1198/tast.2010.09004.

Model misspecification in peaks over threshold analysis

M. Süveges; A. C. Davison 

The Annals of Applied Statistics. 2010. Vol. 4, num. 1, p. 203 – 221. DOI : 10.1214/09-AOAS292.

Revisiting the Edge, Ten Years On

V. Chavez-Demoulin; P. Embrechts 

Communications In Statistics-Theory And Methods. 2010. Vol. 39, p. 1674 – 1688. DOI : 10.1080/03610920902822670.

2009

Fast high-dimensional Bayesian classification and clustering

V. Partovi Nia / A. C. Davison (Dir.)  

Lausanne, EPFL, 2009. 

The radial plot in meta-analysis: approximations and applications

J. Copas; C. Lozada-Can 

Journal Of The Royal Statistical Society Series C-Applied Statistics. 2009. Vol. 58, p. 329 – 344. DOI : 10.1111/j.1467-9876.2008.00650.x.

Global sensitivity analysis of computer models with functional inputs

B. Iooss; M. Ribatet 

2009. 5th International Conference on Sensitivity Analysis of Model Output (SAMO 2007), Budapest, HUNGARY, Jun 18-22, 2007. p. 1194 – 1204. DOI : 10.1016/j.ress.2008.09.010.

Proteogenomic studies in epithelial ovarian cancer: established knowledge and future needs

F. Jacob; D. R. Goldstein; D. Fink; V. Heinzelmann-Schwarz 

Biomarkers In Medicine. 2009. Vol. 3, p. 743 – 756. DOI : 10.2217/BMM.09.48.

A note on the representation of parametric models for multivariate extremes

M-O. Boldi 

Extremes. 2009. Vol. 12, p. 211 – 218. DOI : 10.1007/s10687-008-0076-0.

Statistical analysis of clusters of extreme events

M. Süveges / A. C. Davison (Dir.)  

Lausanne, EPFL, 2009. 

Alignment of Multiple Configurations Using Hierarchical Models

Y. Ruffieux; P. J. Green 

Journal of Computational and Graphical Statistics. 2009. Vol. 18, num. 3, p. 756 – 773. DOI : 10.1198/jcgs.2009.07048.

Saddlepoint approximation for mixture models

A. C. Davison; D. Mastropietro 

Biometrika. 2009. Vol. 96, p. 479 – 486. DOI : 10.1093/biomet/asp022.

Stochastic modelling of prey depletion processes

T. Clerc; A. C. Davison; L-F. Bersier 

Journal of Theoretical Biology. 2009. Vol. 259, p. 523 – 532. DOI : 10.1016/j.jtbi.2009.04.017.

2008

Entrainment and motion of coarse particles in a shallow water stream down a steep slope

C. Ancey; A. C. Davison; T. B. Böhm; M. Jodeau; P. FREY 

Journal of Fluid Mechanics. 2008. Vol. 595, p. 83 – 114. DOI : 10.1017/S0022112007008774.

A tutorial on adaptive MCMC

C. Andrieu; J. Thoms 

Statistics And Computing. 2008. Vol. 18, p. 343 – 373. DOI : 10.1007/s11222-008-9110-y.

A Consistent Confidence Interval for Fuzzy Capability Index

A. Parchami; M. Mashinchi; V. Partovi Nia 

Applied and Computational Mathematics. 2008. Vol. 7, num. 1, p. 119 – 125.

The Banff challenge: Statistical detection of a noisy signal

A. C. Davison; N. Sartori 

Statistical Science. 2008. Vol. 23, num. 3, p. 354 – 364. DOI : 10.1214/08-STS260.

Statistical methods for insect choice experiments

I. Ricard / A. C. Davison (Dir.)  

Lausanne, EPFL, 2008. 

Some challenges for statistics

A. C. Davison 

Statistical Methods and Applications. 2008. Vol. 17, p. 167 – 181. DOI : 10.1007/s10260-007-0079-z.

Quality Assessment for Short Oligonucleotide Microarray Data: Comment

D. R. Goldstein 

Technometrics. 2008. Vol. 50, p. 276 – 279. DOI : 10.1198/004017008000000370.

Accurate parametric inference for small samples

A. R. Brazzale; A. C. Davison 

Statistical Science. 2008. Vol. 23, num. 4, p. 465 – 484. DOI : 10.1214/08-STS273.

2007

Reliable confidence intervals in quantitative genetics: Narrow-sense heritability

T. Fabbro; A. C. Davison; T. Steinger 

Theoretical and Applied Genetics. 2007. Vol. 115, p. 933 – 944. DOI : 10.1007/s00122-007-0619-9.

Applied Asymptotics: Case Studies in Small-Sample Statistics

A. R. Brazzale; A. C. Davison; N. Reid 

Cambridge: Cambridge University Press, 2007.

Likelihood estimation of the extremal index

M. Suveges 

Extreme-Value Analysis, Bern, Switzerland, 23-27 July 2007.

Statistical inference for olfactometer data

I. Ricard; A. C. Davison 

Applied Statistics. 2007. Vol. 56, p. 479 – 492. DOI : 10.1111/j.1467-9876.2007.00588.x.

Likelihood estimation of the extremal index

M. Suveges 

Statistics of Extremes and Environmental Risk, Lisbon, Portugal, 14-18 February 2007.

An Intorduction to the Interface Between C and R

A. Chaudhary 

2007

Likelihood estimation of the extremal index

M. Süveges 

Extremes. 2007. Vol. 10, num. 1-2, p. 41 – 55. DOI : 10.1007/s10687-007-0034-2.

Resamping variance estimation in surveys with missing data

A. C. Davison; S. Sardy 

Journal of Offical Statistics. 2007. Vol. 23, p. 371 – 386.

A mixture model for multivariate extremes

M-O. Boldi; A. C. Davison 

Journal of the Royal Statistical Society, series B. 2007. Vol. 69, p. 217 – 229. DOI : 10.1111/j.1467-9868.2007.00585.x.

Hierarchical wavelet modelling of environmental sensor data

Y. Ruffieux; A. C. Davison 

2007

Rapid Classification of Phenotypic Mutants of Arabidopsis via Metabolite Fingerprinting

G. Messerli; V. Partovi Nia; M. Trevisan; A. Kolbe; N. Schauer et al. 

Plant Physiology. 2007. Vol. 143, p. 1484 – 1492. DOI : 10.1104/pp.106.090795.

Conserved oviposition preferences in alpine leaf beetle populations despite host shifts and isolation

A. Verdon; N. Margraf; A. C. Davison; M. Rahier; R. E. Naisbit 

Ecological Entomology. 2007. Vol. 32, p. 62 – 69. DOI : 10.1111/j.1365-2311.2006.00842.x.

Some Basic Functions for Tree Representations of Bayesian Markov Chain Monte Carlo Clustering

A. Chaudhary; V. Partovi Nia; A. C. Davison 

2007

2006

A comparison of naive and conditioned responses of three generalist endoparasitoids of lepidopteran larvae to host-induced plant odours

C. Tamò; I. Ricard; M. Held; A. C. Davison; T. C. J. Turlings 

Animal Biology. 2006. Vol. 56, p. 205 – 220. DOI : 10.1163/157075606777304177.

Bayesian forecasting of grape moth emergence

M-A. Moravie; A. C. Davison; D. Pasquier; P-J. Charmillot 

Ecological Modelling. 2006. Vol. 197, p. 478 – 489. DOI : 10.1016/j.ecolmodel.2006.03.030.

Méthodes de rééchantillonnage pour l’estimation de variance

A. C. Davison; S. Sardy 

Journal de la Société Française de Statistique. 2006. Vol. 147, num. 3, p. 3 – 32.

Improved likelihood inference for discrete data

A. C. Davison; D. A. S. Fraser; N. Reid 

Journal of the Royal Statistical Society series B. 2006. Vol. 68, p. 495 – 508. DOI : 10.1111/j.1467-9868.2006.00548.x.

A Laplace mixture model for the identification of differential expression in microarrays

D. Bhowmick; A. C. Davison; D. R. Goldstein; Y. Ruffieux 

Biostatistics. 2006. Vol. 7, num. 4, p. 630 – 641. DOI : 10.1093/biostatistics/kxj032.

Survival and Censored Data

L. Samartzis 

2006

Bootstrap diagnostics and remedies

A. J. Canty; A. C. Davison; D. V. Hinkley; V. Ventura 

Canadian Journal of Statistics. 2006. Vol. 34, p. 5 – 27. DOI : 10.1002/cjs.5550340103.

Clustering of extreme temperatures from 1772 to 2004

M. Suveges; A. C. Davison 

Global Change Day 2006, Bern, Switzerland, 2006-04-20.

Partition resampling and extrapolation averaging: approximation methods for quantifying gene expression in large numbers of short oligonucleotide arrays

D. R. Goldstein 

Bioinformatics. 2006. Vol. 22, num. 19, p. 2364 – 2372. DOI : 10.1093/bioinformatics/btl402.

Assessment and analysis of mechanical allodynia-like behaviour induced by spared nerve injury (SNI) in the mouse

A-F. Bourquin; M. Süveges; M. Pertin; N. Gilliard; S. Sardy et al. 

Pain. 2006. Vol. 122, num. 1-2, p. 14e1 – 14.e14. DOI : 10.1016/j.pain.2005.10.036.

Bayesian risk analysis of financial time series

C. Osinski / A. C. Davison (Dir.)  

Lausanne, EPFL, 2006. 

2005

Celebrating Statistics: Papers in Honour of Sir David Cox on the Occasion of his 80th Birthday

A. C. Davison; Y. Dodge; N. Wermuth 

Oxford, UK: Oxford University Press, 2005.

The evaluation of evidence in the forensic investigation of fire incidents (Part I): An approach using Bayesian networks

A. Biedermann; F. Taroni; O. Delemont; C. Semadeni; A. C. Davison 

Forensic Science International. 2005. Vol. 147, p. 49 – 57. DOI : 10.1016/j.forsciint.2004.04.014.

Generalized monotone additive latent variable models

M-P. Victoria-Feser; S. Sardy 

2005

Saddlepoint approximations to studentized bootstrap distributions based on M-estimates

D. Kuonen 

Computational Statistics. 2005. Vol. 20, num. 2, p. 231 – 244. DOI : 10.1007/BF02789701.

Identification of molecular apocrine breast tumours by microarray analysis

P. Farmer; H. Bonnefoi; V. Becette; M. Tubiana-Hulin; P. Fumoleau et al. 

Oncogene. 2005. Vol. 24, num. 29, p. 4660 – 71. DOI : 10.1038/sj.onc.1208561.

The evaluation of evidence in the forensic investigation of fire incidents (Part II): Practical examples of the use of Bayesian networks

A. Biedermann; F. Taroni; O. Delemont; C. Semadeni; A. C. Davison 

Forensic Science International. 2005. Vol. 147, p. 59 – 69. DOI : 10.1016/j.forsciint.2004.04.015.

Studentized bootstrap confidence intervals based on M-estimates

D. Kuonen 

Journal of Applied Statistics. 2005. Vol. 32, num. 5, p. 443 – 460. DOI : 10.1080/02664760500079340.

Generalized additive models for sample extremes

V. Chavez-Demoulin; A. C. Davison 

Applied Statistics. 2005. Vol. 54, p. 207 – 222. DOI : 10.1111/j.1467-9876.2005.00479.x.

Bootstrap methods

A. J. Canty; A. C. Davison 

Encyclopedia of Statistics in the Behavioural Sciences; Wiley, 2005. p. 169 – 176.

Gene Expression Measurements by Quantitative Real-time PCR Depends on Short Amplicons and a Proper Normalization

J. Antonov; D. R. Goldstein; A. Oberli; A. Baltzer; M. Pirotta et al. 

Laboratory Investigation. 2005. Vol. 85, p. 1040 – 1050. DOI : 10.1038/labinvest.3700303.

A point process approach to value-at-risk estimation

V. Chavez-Demoulin; A. C. Davison; A. J. McNeil 

Quantitative Finance. 2005. Vol. 5, num. 2, p. 227 – 234. DOI : 10.1080/14697680500039613.

2004

Resampling-based variance estimation in DACSEIS with application to the Swiss Household Budget Survey

A. Davison; S. Sardy 

2004. 

Extreme values

A. C. Davison 

Encyclopedia of Biostatistics; Wiley, 2004.

Unraveling Lipid Metabolism with Micorarrays

D. R. Goldstein; M. Delorenzi 

Statistical Design and Data Analysis for Microarray Experiments; Dekker, 2004.

AMlet, RAMlet and GAMlet: Automatic nonlinear fitting of additive models, robust and generalized with wavelets

S. Sardy; P. Tseng 

Journal of Computational and Graphical Statistics. 2004. Vol. 13, p. 283 – 309. DOI : 10.1198/1061860043434.

Structure and inferred dynamics of a large grove of Microberlinia bisulcata trees in central African rain forest: the possible role of periods of multiple disturbance events

D. M. Newbery; X. M. van der Burgt; M-A. Moravie 

Journal of Tropical Ecology. 2004. Vol. 20, num. 2, p. 131 – 143. DOI : 10.1017/S0266467403001111.

Automatic smoothing with wavelets for a wide class of distributions

S. Sardy; A. Antoniadis; P. Tseng 

Journal of Computational and Graphical Statistics. 2004. Vol. 13, p. 399 – 421. DOI : 10.1198/1061860043399.

A six-arm olfactometer permitting simultaneous observation of insect attraction and odour trapping

T. C. J. Turlings; C. Tamo; A. C. Davison 

Physiological Entomology. 2004. Vol. 29, num. 1, p. 1 – 11. DOI : 10.1111/j.1365-3032.2004.0362.x.

Normal Scores

A. C. Davison 

Encyclopedia of Biostatistics; Wiley, 2004.

Numerical integration is an art, not a science

D. Kuonen 

Bulletin of the International Society for Bayesian Analysis. 2004. Vol. 11, num. 1, p. 11 – 13.

On the statistical analysis of smoothing by maximizing dirty Markov random field posterior distributions

S. Sardy; P. Tseng 

Journal of the American Statistical Association. 2004. Vol. 9, p. 191 – 204. DOI : 10.1198/016214504000000188.

Posterior probability intervals in Bayesian wavelet estimation

C. Semadeni; A. C. Davison; D. V. Hinkley 

Biometrika. 2004. Vol. 91, num. 2, p. 497 – 505. DOI : 10.1093/biomet/91.2.497.

Mixture models for multivariate extremes

M-O. Boldi / A. C. Davison (Dir.)  

Lausanne, EPFL, 2004. 

Order statistics

A. C. Davison; F. Dorsaz 

Encyclopedia of Biostatistics; Wiley, 2004.

2003

Discussion of Kong, A., McCullagh, P., Nicolae, D., Tan, Z., and Meng, X.-L. (2003) A theory of statistical models for Monte Carlo integration

A. C. Davison 

Journal of the Royal Statistical Society series B. 2003. Vol. 65, p. 609.

A brief introduction to genetics

D. R. Goldstein 

Science and Statistics: A Festschrift for Terry Speed; 2003. p. 231 – 236.

Natural variation in baseline data: when do we call a new sample ‘resistant’?

L. Schaub; S. Sardy; G. Capkun 

2003. 

Extensions to a score test for genetic linkage with identity by descent data

S. Dudoit; D. R. Goldstein 

Science and Statistics: A Festschrift for Terry Speed; 2003. p. 307 – 319.

Discussion of Heffernan, J. and Tawn, J. A. (2004) A conditional approach for multivariate extreme values

M-O. Boldi; A. C. Davison 

Journal of the Royal Statistical Society series B. 2003. Vol. 66, p. 539 – 540.

Household smoking behavior and ETS exposure among children with asthma in low-income, minority households

B. A. Berman; G. C. Wong; R. Bastani; T. Hoang; C. Jones et al. 

Addictive Behaviors. 2003. Vol. 28, num. 1, p. 111 – 128. DOI : 10.1016/S0306-4603(01)00221-0.

A note on model uncertainty in linear regression

C. Candolo; A. C. Davison; C. G. B. Demétrio 

The Statistician. 2003. Vol. 52, p. 165 – 177. DOI : 10.1111/1467-9884.00349.

Discussion of Wakefield, J. (2004) Ecological inference for 2×2 tables

A. C. Davison; C. Semadeni 

Journal of the Royal Statistical Society series A. 2003. Vol. 167, p. 434 – 435.

Statistical Models

A. C. Davison 

Cambridge: Cambridge University Press, 2003.

Numerical integration in S-PLUS or R: a survey

D. Kuonen 

Journal of Statistical Software. 2003. Vol. 8, p. 1 – 14. DOI : 10.18637/jss.v008.i13.

The Oxford Dictionary of Statistical Terms

D. R. Cox; D. Commenges; A. C. Davison; P. J. Solomon; S. R. Wilson 

The Oxford Dictionary of Statistical Terms; Oxford University Press, 2003.

Non-parametric bootstrap confidence intervals for the intraclass correlation coefficient

O. C. Ukoumunne; A. C. Davison; M. C. Gulliford; S. Chinn 

Statistics in Medicine. 2003. Vol. 22, num. 24, p. 3805 – 3821. DOI : 10.1002/sim.1643.

Topographic variation and stand heterogeneity in a wet evergreen forest of India

M-A. Moravie; A. Robert 

Journal of Tropical Ecology. 2003. Vol. 19, num. 6, p. 697 – 707. DOI : 10.1017/S0266467403006096.

Recent developments in bootstrap methodology

A. C. Davison; D. V. Hinkley; G. A. Young 

Statistical Science. 2003. Vol. 18, p. 141 – 157. DOI : 10.1214/ss/1063994969.

Resampling-based variance estimation in DACSEIS

A. C. Davison; S. Sardy 

Bulletin of the International Statistical Institute: Data quality in complex surveys, Berlin. 2003. 

A model to assess relationships between forest dynamics and spatial structure

M-A. Moravie; A. Robert 

Journal of Vegetation Science. 2003. Vol. 14, p. 823 – 834. DOI : 10.1111/j.1654-1103.2003.tb02215.x.

2002

Empirical supremum rejection sampling

B. Caffo; J. G. Booth; A. C. Davison 

Biometrika. 2002. Vol. 89, num. 4, p. 745 – 754. DOI : 10.1093/biomet/89.4.745.

Discussion of K. W. Broman and T. P. Speed (2002) A model selection approach for the identification of quantitative trait loci in experimental crosses and G. Parmigiani, E. S. Garrett, R. Anbazhagan, and E. Gabrielson (2002) A statistical framework for expression-based molecular classification in cancer

D. R. Goldstein 

Journal of the Royal Statistical Society series B. 2002. Vol. 64, p. 744.

Natural variation in baseline data: when do we call a new sample “resistant”?

L. Schaub; S. Sardy; G. Capkun 

Pest Management Science. 2002. Vol. 58, num. 10, p. 959 – 963. DOI : 10.1002/ps.561.

Effects of dinoseb on the life cycle of Daphnia magna : modeling survival time and a proposal for an alternative to the no-observed-effect concentration

N. Chèvre; K. Becker-Van Slooten; J. Tarradellas; A. Brazzale; R. Behra et al. 

Environmental Toxicology and Chemistry. 2002. Vol. 21, num. 4, p. 828 – 833. DOI : 10.1002/etc.5620210420.

Local models for exploratory analysis of hydrological extremes

N. I. Ramesh; A. C. Davison 

Journal of Hydrology. 2002. Vol. 256, num. 1–2, p. 106 – 119. DOI : 10.1016/S0022-1694(01)00522-4.

A comparison between L_1 Markov random field-based and wavelet-based estimators

S. Sardy; C. Bilat; P. Tseng; V. Chavez-Demoulin 

Statistical Data Analysis Based on the L1-Norm and Related Methods; Birkhäuser, 2002. p. 395 – 403.

Performance of quantitative versus passive investing: a comparison in global markets

R. C. Dalang; C. Osinski; W. Marty 

The Journal of Performance Measurement. 2002. Vol. 6, num. 2, p. 29 – 44.

Saddlepoint approximations as smoothers

A. C. Davison; S. Wang 

Biometrika. 2002. Vol. 89, num. 4, p. 933 – 938. DOI : 10.1093/biomet/89.4.933.

An introduction to the bootstrap with applications in R

A. C. Davison; D. Kuonen 

Statistical Computing and Graphics Newsletter. 2002. Vol. 13, p. 6 – 11.

2001

Computer-intensive statistical methods : saddlepoint approximations with applications in bootstrap and robust inference

D. Kuonen / A. C. Davison (Dir.)  

Lausanne, EPFL, 2001. 

Regression diagnostics

A. C. Davison 

Encyclopedia of Environmetrics; Wiley, 2001. p. 1728 – 1733.

GRASS GIS et R : main dans la main dans un monde libre

R. Furrer; D. Kuonen 

Flash Informatique. 2001. num. Spécial Été, p. 51 – 56.

R – un exemple du succès des modèles libres

D. Kuonen; V. Chavez-Demoulin 

Flash Informatique. 2001. Vol. 2, p. 3 – 7.

Identity-by-descent sharing using Markov chain Monte Carlo in subsets of the asthma Hutterite pedigree

C. M. Greenwood; A. Bureau; J. C. Loredo-Osti; N. M. Roslin; M. J. Crumley et al. 

Genetic Epidemiology. 2001. Vol. 21, Suppl., p. 244 – 251.

A computer algebra package for approximate conditional inference

R. Bellio; A. Brazzale 

Statistics and Computing. 2001. Vol. 11, num. 1, p. 17 – 24. DOI : 10.1023/A:1026501714434.

Statistical issues in the clustering of gene expression data

D. R. Goldstein; D. Ghosh; E. M. Conlon 

Statistica Sinica. 2001. Vol. 12, p. 219 – 240.

T-cell immune activation in children with vertically transmitted hepatitis C virus infection

A. Giovannetti; F. Mazzetta; R. Coviello; A. M. Casadei; S. Mattia et al. 

Viral Immunology. 2001. Vol. 14, p. 169 – 179. DOI : 10.1089/088282401750234547.

A wolf habitat suitability prediction study in Valais (Switzerland)

C. Glenz; A. Massolo; D. Kuonen; R. Schlaepfer 

Landscape and Urban Planning. 2001. Vol. 55, num. 1, p. 55 – 65. DOI : 10.1016/S0169-2046(01)00119-0.

Robust wavelet denoising

S. Sardy; P. Tseng; A. Bruce 

IEEE Transactions on Signal Processing. 2001. Vol. 49, num. 6, p. 1146 – 1152. DOI : 10.1109/78.923297.

T cell responses to highly active antiretroviral therapy defined by chemokine receptors expression, cytokine production, T cell receptor repertoire and anti-HIV T-lymphocyte activity

A. Giovannetti; M. Pierdominici; F. Mazzetta; S. Salemi; M. Marziali et al. 

Clinical and Experimental Immunology. 2001. Vol. 124, num. 1, p. 21 – 31. DOI : 10.1046/j.1365-2249.2001.01502.x.

Data mining avec R dans un monde libre

R. Furrer; D. Kuonen 

Flash Informatique. 2001. num. Spécial Été, p. 45 – 50.

A Robust Rainfall-Runoff Transfer Model

G. Capkun; A. C. Davison; A. Musy 

Water Resources Research. 2001. Vol. 37, num. 12, p. 3207 – 3216. DOI : 10.1029/2001WR000295.

Biometrika centenary: Theory and general methodology

A. C. Davison 

Biometrika. 2001. Vol. 88, num. 1, p. 13 – 52. DOI : 10.1093/biomet/88.1.13.

Power and robustness of a score test for linkage analysis of quantitative traits using identity by descent data on sib pairs

D. R. Goldstein; S. Dudoit; T. P. Speed 

Genetic Epidemiology. 2001. Vol. 20, num. 4, p. 415 – 431. DOI : 10.1002/gepi.1011.

2000

Parallel processing in statistical computation : BSP, FPGas and MPI for the S-language

A. Röhrl / A. C. Davison (Dir.)  

Lausanne, EPFL, 2000. 

Power of a score test for quantitative trait linkage analysis of relative pairs

D. R. Goldstein; S. Dudoit; T. P. Speed 

Genetic Epidemiology. 2000. Vol. 19, num. s1, p. 585 – 591. DOI : 10.1002/1098-2272(2000)19:1+<::AID-GEPI13>3.0.CO;2-7.

Local likelihood smoothing of sample extremes

A. C. Davison; N. I. Ramesh 

Journal of the Royal Statistical Society series B. 2000. Vol. 62, p. 191 – 208. DOI : 10.1111/1467-9868.00228.

Intervalles de confiance bootstrap studentisésbasés sur des M-estimateurs robustes utilisant des approximationsde point de selle

D. Kuonen 

2000.  p. 501 – 502.

Block coordinate relaxation methods for nonparametric wavelet denoising

S. Sardy; A. G. Bruce; P. Tseng 

Journal of Computational and Graphical Statistics. 2000. Vol. 9, p. 361 – 379. DOI : 10.1080/10618600.2000.10474885.

A familial risk profile for osteoporosis

L. B. Henderson; J. S. Adams; D. R. Goldstein; G. D. Braunstein; J. I. Rotter et al. 

Genetics in Medicine. 2000. Vol. 2, p. 222 – 225. DOI : 10.1097/00125817-200007000-00004.

Minimax threshold for denoising complex signals with Waveshrink

S. Sardy 

IEEE Transactions on Signal Processing. 2000. Vol. 48, num. 4, p. 1023 – 1028. DOI : 10.1109/78.827536.

Practical small-sample parametric inference

A. R. Brazzale / A. C. Davison (Dir.)  

Lausanne, EPFL, 2000. 

Inference for the poly-Weibull model

A. C. Davison; F. Louzada-Neto 

The Statistician. 2000. Vol. 49, p. 189 – 196. DOI : 10.1111/1467-9884.00229.

Contribution to the discussion of `The estimating function bootstrap’ by F. Hu and J. D. Kalbfleisch

A. J. Canty; A. C. Davison 

Canadian Journal of Statistics. 2000. Vol. 28, p. 488 – 493.

T cell responses to highly active antiretroviral therapy defined by chemokine receptors expression, cytokine production, T cell receptor repertoire and anti-HIV T-lymphocyte activity

A. Giovannetti; M. Pierdominici; F. Mazzetta; S. Salemi; M. Marziali et al. 

2000. 

Was France’s World Cup win pure chance?

D. Kuonen; A. S. A. Röhrl 

Student. 2000. Vol. 3, p. 153 – 166.

Improvement of CD4, but not CD8, TCR BV repertoire after HAART

A. Giovannetti; D. Kuonen; F. Mazzetta; F. Iebba; E. A. Lusi et al. 

2000. 

Contemporary evaluation of T cell subsets, chemokine receptors expression, cytokine production, anti-HIV cytotoxic activity and TCR V-beta repertoire in HIV-1-infected individuals during HAART

A. Giovannetti; M. Pierdominici; F. Mazzetta; S. Salemi; M. Marziali et al. 

2000. 

Wavestrapping time series: Adaptive wavelet-based bootstrapping

D. B. Percival; S. Sardy; A. C. Davison 

Nonlinear and Nonstationary Signal Processing; Cambridge University Press, 2000. p. 442 – 471.

Contemporary evaluation of T cell subsets, chemokine receptors expression, cytokine production, anti-HIV cytotoxic activity and TCR V-beta repertoire in HIV-1-infected individuals during HAART

A. Giovannetti; M. Pierdominici; F. Mazzetta; M. M. S. Salemi; D. Kuonen et al. 

Minerva Biotecnologica. 2000. Vol. 12, p. 196.

A saddlepoint approximation for the collector’s problem

D. Kuonen 

The American Statistician. 2000. Vol. 54, p. 165 – 169. DOI : 10.1080/00031305.2000.10474540.

1999

Saddlepoint approximations for distributions of quadratic forms in normal variables

D. Kuonen 

Biometrika. 1999. Vol. 86, num. 4, p. 929 – 935. DOI : 10.1093/biomet/86.4.929.

Two problems in environmental statistics : capture-recapture analysis and smooth extremal models

V. Chavez / A. C. Davison (Dir.)  

Lausanne, EPFL, 1999. 

The bootstrap: A tutorial

A. C. Davison; H. Friedl; A. Berghold; G. Kauermann 

1999.  p. 10 – 18.

Wavelet de-noising for unequally spaced data

S. Sardy; A. G. Bruce; P. Tseng 

Statistics and Computing. 1999. Vol. 9, num. 1, p. 65 – 75. DOI : 10.1023/A:1008818328241.

Resampling-based variance estimation for labour force surveys

A. J. Canty; A. C. Davison 

The Statistician. 1999. Vol. 48, p. 379 – 391. DOI : 10.1111/1467-9884.00196.

1998

Extreme values

A. C. Davison 

Encyclopedia of Biostatistics; Wiley, 1998. p. 1463 – 1467.

Implementation of saddlepoint approximations in resampling problems

A. J. Canty; A. C. Davison 

Statistics and Computing. 1998. Vol. 9, p. 9 – 15. DOI : 10.1023/A:1008801807768.

1997

Bootstrap Methods and Their Application

A. C. Davison; D. V. Hinkley 

Cambridge: Cambridge University Press, 1997.

1996

Some models for discretized series of events

A. C. Davison; N. I. Ramesh 

Journal of the American Statistical Association. 1996. Vol. 91, p. 601 – 609. DOI : 10.1080/01621459.1996.10476929.

Reliable confidence intervals. Discussion of “Bootstrap confidence intervals”, by T. J. DiCiccio and B. Efron

A. J. Canty; A. C. Davison; D. V. Hinkley 

Statistical Science. 1996. Vol. 11, p. 214 – 219.

Implementation of saddlepoint approximations to bootstrap distributions

A. J. Canty; A. C. Davison; L. Billard; N. I. Fisher 

1996.  p. 248 – 253.