Publications

2024

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. 

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 C-Applied Statistics. 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 A-Statistics In Society. 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.

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.

Gradient boosting with extreme-value theory for wildfire prediction

J. Koh 

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

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.

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.

Spatiotemporal modelling of extreme wildfires and severe thunderstorm environments

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

Lausanne, EPFL, 2022. 

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Contributions to Likelihood-Based Modelling of Extreme Values

L. Raymond-Belzile / 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. 

Automatic L2 Regularization for Multiple Generalized Additive Models

Y. El Bachir / A. C. Davison (Dir.)  

Lausanne, EPFL, 2019. 

Fast Automatic Smoothing for Generalized Additive Models

Y. El-Bachir; A. C. Davison 

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

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. 

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.

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.

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.

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.

Contributions to Modelling Extremes of Spatial Data

L. Frossard / A. C. Davison (Dir.)  

Lausanne, EPFL, 2017. 

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.

A Functional Framework for Enhanced Ultrasound Imaging

L. Roquette 

2017.

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.

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.

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.

ODE parameter estimation through a runner’s model application

L. Roquette 

2016.

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.

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.

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.

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.

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.

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.

2015

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.

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.

Objective Bayesian Model Selection

T. Lugrin 

2015

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.

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.

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.

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.

Meta-analysis of Incomplete Microarray Studies

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

Lausanne, EPFL, 2014. 

Contributions to Spatial Statistics : Species Distributions and Rare Events

E. Thibaud / A. C. Davison (Dir.)  

Lausanne, EPFL, 2014. 

Additive Smooth Modelling with Splines

T. Lugrin 

2014

Heavy-tail Phenomena: Spatio-temporal Extremal Dependence

T. Lugrin 

2014

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Statistical Modeling and Inference for Spatio-Temporal Extremes

R. Huser / A. C. Davison (Dir.)  

Lausanne, EPFL, 2013. 

Bayesian Semiparametrics for Modelling the Clustering of Extreme Values

T. Lugrin 

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.

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.

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.

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.

Bivariate Extreme Statistics, Ii

M. de Carvalho; A. Ramos 

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

Modelling Time Series Extremes

V. Chavez-Demoulin; A. C. Davison 

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

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.

Statistical Analysis of Mountain Permafrost Temperatures

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

Lausanne, EPFL, 2012. 

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.

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.

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.

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.

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.

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.

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.

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.

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.

Extremes: spatial parametric modeling

A. C. Davison 

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

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.

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.

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

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.

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 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.

Statistics of extremes

M. Lovric; A. C. Davison 

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

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.

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

A. C. Davison 

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

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.

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.

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.

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.

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.

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.

Geostatistics of Extremes : A Composite Likelihood Approach

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

Lausanne, EPFL, 2010. 

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.

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.

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.

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.

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.

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.

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.

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.

2009

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.

Fast high-dimensional Bayesian classification and clustering

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

Lausanne, EPFL, 2009. 

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.

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.

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.

Saddlepoint approximation for mixture models

A. C. Davison; D. Mastropietro 

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

Statistical analysis of clusters of extreme events

M. Süveges / 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.

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.

2008

Quality Assessment for Short Oligonucleotide Microarray Data: Comment

D. R. Goldstein 

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

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.

Some challenges for statistics

A. C. Davison 

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

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. 

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.

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.

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. Süveges 

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

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

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

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.

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.

Likelihood estimation of the extremal index

M. Suveges 

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

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.

Likelihood estimation of the extremal index

M. Suveges 

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

Hierarchical wavelet modelling of environmental sensor data

Y. Ruffieux; A. C. Davison 

2007

An Intorduction to the Interface Between C and R

A. Chaudhary 

2007

Applied Asymptotics: Case Studies in Small-Sample Statistics

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

Cambridge: Cambridge University Press, 2007.

Resamping variance estimation in surveys with missing data

A. C. Davison; S. Sardy 

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

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.

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.

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.

Bayesian risk analysis of financial time series

C. Osinski / A. C. Davison (Dir.)  

Lausanne, EPFL, 2006. 

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.

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.

Clustering of extreme temperatures from 1772 to 2004

M. Suveges; A. C. Davison 

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

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.

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.

Survival and Censored Data

L. Samartzis 

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.

2005

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.

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.

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.

Bootstrap methods

A. J. Canty; A. C. Davison 

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

Generalized monotone additive latent variable models

M-P. Victoria-Feser; S. Sardy 

2005

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.

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.

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 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.

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.

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.

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.

Extreme values

A. C. Davison 

Encyclopedia of Biostatistics; Wiley, 2004.

Mixture models for multivariate extremes

M-O. Boldi / A. C. Davison (Dir.)  

Lausanne, EPFL, 2004. 

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

A. Davison; S. Sardy 

2004. 

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.

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.

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.

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.

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.

Unraveling Lipid Metabolism with Micorarrays

D. R. Goldstein; M. Delorenzi 

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

Normal Scores

A. C. Davison 

Encyclopedia of Biostatistics; Wiley, 2004.

Order statistics

A. C. Davison; F. Dorsaz 

Encyclopedia of Biostatistics; Wiley, 2004.

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.

2003

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.

A brief introduction to genetics

D. R. Goldstein 

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

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.

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

L. Schaub; S. Sardy; G. Capkun 

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.

Statistical Models

A. C. Davison 

Cambridge: Cambridge University Press, 2003.

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 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.

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.

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.

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.

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.

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.

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.

2002

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

R – un exemple du succès des modèles libres

D. Kuonen; V. Chavez-Demoulin 

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

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.

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.

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.

Data mining avec R dans un monde libre

R. Furrer; D. Kuonen 

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

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.

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.

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.

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

Practical small-sample parametric inference

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

Lausanne, EPFL, 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.

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

A. Röhrl / A. C. Davison (Dir.)  

Lausanne, EPFL, 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. 

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

D. Kuonen 

2000.  p. 501 – 502.

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. 

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. 

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.

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 saddlepoint approximation for the collector’s problem

D. Kuonen 

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

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.

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.

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.

Was France’s World Cup win pure chance?

D. Kuonen; A. S. A. Röhrl 

Student. 2000. Vol. 3, p. 153 – 166.

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.

1999

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.

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.

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.

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.

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

Implementation of saddlepoint approximations to bootstrap distributions

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

1996.  p. 248 – 253.

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.