2025
Structural equation models for multivariate extremes
Lausanne, EPFL, 2025.Non-regular Inference: Universal Inference and Discrete Profiling
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.
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
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
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
Journal Of The Royal Statistical Society Series B-Statistical Methodology. 2024. Vol. 86, num. 1. DOI : 10.1093/jrsssb/qkad118.Space-Time Extremes of Severe U.S. Thunderstorm Environments
Journal of the American Statistical Association. 2024. DOI : 10.1080/01621459.2024.2421582.Flexible Statistical Inference for Multivariate Extremes
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’
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
Canadian Journal Of Statistics-Revue Canadienne De Statistique. 2023. DOI : 10.1002/cjs.11791.Timing and spatial selection bias in rapid extreme event attribution
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
Iscience. 2023. Vol. 26, num. 6, p. 106740. DOI : 10.1016/j.isci.2023.106740.Some Reminiscences of David Cox
HARVARD DATA SCIENCE REVIEW. 2023. num. 2. DOI : 10.1162/99608f92.85038493.Gradient boosting with extreme-value theory for wildfire prediction
Extremes. 2023. DOI : 10.1007/s10687-022-00454-6.Spatiotemporal wildfire modeling through point processes with moderate and extreme marks
The Annals of Applied Statistics. 2023. Vol. 17, num. 1, p. 560 – 582. DOI : 10.1214/22-AOAS1642.Higher Order Asymptotics: Applications to Satellite Conjunction and Boundary Problems
Lausanne, EPFL, 2023.Wind, Hail, and Climate Extremes: Modelling and Attribution Studies for Environmental Data
Lausanne, EPFL, 2023.2022
Causal modelling of heavy-tailed variables and confounders with application to river flow
Extremes. 2022. DOI : 10.1007/s10687-022-00456-4.A note on universal inference
Stat. 2022. Vol. 11, num. 1, p. e501. DOI : 10.1002/sta4.501.Downscaling of Historical Wind Fields over Switzerland Using Generative Adversarial Networks
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
Journal Of Guidance Control And Dynamics. 2022. DOI : 10.2514/1.G006282.Stochastic derivative estimation for max-stable random fields
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
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
Journal Of Business & Economic Statistics. 2022. DOI : 10.1080/07350015.2022.2078332.Functional peaks-over-threshold analysis
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
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
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
Lausanne, EPFL, 2022.Is There a Cap on Longevity? A Statistical Review
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
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
Bmj Open. 2021. Vol. 11, num. 12, p. e053070. DOI : 10.1136/bmjopen-2021-053070.Human mortality at extreme age
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
Stat. 2021. Vol. 10, num. 1, p. e401. DOI : 10.1002/sta4.401.Predicting involuntary hospitalization in psychiatry: A machine learning investigation
European Psychiatry. 2021. Vol. 64, num. 1, p. e48. DOI : 10.1192/j.eurpsy.2021.2220.Practical issues with modeling extreme Brazilian rainfall
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
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
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
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
Biometrics. 2021. Vol. 77, p. 186 – 196. DOI : 10.1111/biom.13282.Multivariate extremes over a random number of observations
Scandinavian Journal Of Statistics. 2021. Vol. 48, num. 3, p. 845 – 880. DOI : 10.1111/sjos.12463.2020
Special Issue: “Data Science versus Classical Inference: Prediction, Estimation, and Attribution”, honouring Prof. Brad Efron’s International Prize in Statistics in 2019 Discussion
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
International Journal of Disaster Risk Reduction. 2020. Vol. 49, p. 101732. DOI : 10.1016/j.ijdrr.2020.101732.Simultaneous autoregressive models for spatial extremes
Environmetrics. 2020. p. e2656. DOI : 10.1002/env.2656.An unethical optimization principle
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
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
Annals Of Applied Statistics. 2020. Vol. 14, num. 2, p. 905 – 928. DOI : 10.1214/20-AOAS1332.Discussion
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
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
Journal Of Theoretical Biology. 2020. Vol. 486, p. 110087. DOI : 10.1016/j.jtbi.2019.110087.Inference on the Angular Distribution of Extremes
Lausanne, EPFL, 2020.2019
Exploration and Inference in Spatial Extremes Using Empirical Basis Functions
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!
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
Annals Of Applied Probability. 2019. Vol. 29, num. 5, p. 2782 – 2818. DOI : 10.1214/19-AAP1464.Decompositions of dependence for high-dimensional extremes
Biometrika. 2019. Vol. 106, num. 3, p. 587 – 604. DOI : 10.1093/biomet/asz028.A central limit theorem for functions of stationary max-stable random fields on R-d
Stochastic Processes And Their Applications. 2019. Vol. 129, num. 9, p. 3406 – 3430. DOI : 10.1016/j.spa.2018.09.014.A nonparametric method for producing isolines of bivariate exceedance probabilities
Extremes. 2019. Vol. 22, num. 3, p. 373 – 390. DOI : 10.1007/s10687-019-00348-0.Fitting Markovian binary trees using global and individual demographic data
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
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
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
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
Biometrika. 2019. Vol. 106, num. 1, p. 127 – 144. DOI : 10.1093/biomet/asy052.Geometric ergodicity for some space-time max-stable Markov chains
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
Nature Communications. 2019. Vol. 10, p. 540. DOI : 10.1038/s41467-019-08492-8.Automatic L2 Regularization for Multiple Generalized Additive Models
Lausanne, EPFL, 2019.Large-scale variational inference for Bayesian joint regression modelling of high-dimensional genetic data
Lausanne, EPFL, 2019.Contributions to Likelihood-Based Modelling of Extreme Values
Lausanne, EPFL, 2019.Fast Automatic Smoothing for Generalized Additive Models
Journal of Machine Learning Research. 2019. Vol. 20, p. 173.2018
Dependence properties of spatial rainfall extremes and areal reduction factors
Journal of Hydrology. 2018. Vol. 565, p. 711 – 719. DOI : 10.1016/j.jhydrol.2018.08.061.High-dimensional peaks-over-threshold inference
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
Extremes. 2018. Vol. 21, num. 3, p. 365 – 372. DOI : 10.1007/s10687-018-0329-5.Automatic module selection from several microarray gene expression studies
BIOSTATISTICS. 2018. Vol. 19, num. 2, p. 153 – 168. DOI : 10.1093/biostatistics/kxx032.Optimal regionalization of extreme value distributions for flood estimation
JOURNAL OF HYDROLOGY. 2018. Vol. 556, p. 182 – 193. DOI : 10.1016/j.jhydrol.2017.10.051.Semiparametric Bayesian Risk Estimation for Complex Extremes
Lausanne, EPFL, 2018.Functional Peaks-Over-Threshold Analysis for Complex Extreme Events
Lausanne, EPFL, 2018.2017
Contributions to Modelling Extremes of Spatial Data
Lausanne, EPFL, 2017.Generalized Pickands constants and stationary max-stable processes
Extremes. 2017. Vol. 20, num. 3, p. 493 – 517. DOI : 10.1007/s10687-017-0289-1.Quasi-random numbers for copula models
Statistics And Computing. 2017. Vol. 27, num. 5, p. 1307 – 1329. DOI : 10.1007/s11222-016-9688-4.A Functional Framework for Enhanced Ultrasound Imaging
2017.Modelling across extremal dependence classes
Journal Of The Royal Statistical Society Series B-Statistical Methodology. 2017. Vol. 79, num. 1, p. 149 – 175. DOI : 10.1111/rssb.12157.Bridging asymptotic independence and dependence in spatial extremes using Gaussian scale mixtures
Spatial Statistics. 2017. Vol. 21, p. 166 – 186. DOI : 10.1016/j.spasta.2017.06.004.Efficient inference for genetic association studies with multiple outcomes
Biostatistics. 2017. Vol. 18, num. 4, p. 618 – 636. DOI : 10.1093/biostatistics/kxx007.Extremal attractors of Liouville copulas
Journal of Multivariate Analysis. 2017. Vol. 160, p. 68 – 92. DOI : 10.1016/j.jmva.2017.05.008.Robust Bounds In Multivariate Extremes
Annals Of Applied Probability. 2017. Vol. 27, num. 6, p. 3706 – 3734. DOI : 10.1214/17-Aap1294.2016
Lyapunov Exponents for Branching Processes in a Random Environment: The Effect of Information
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
Biometrika. 2016. Vol. 103, num. 3, p. 667 – 681. DOI : 10.1093/biomet/asw025.The roles of coupling and the deviation matrix in determining the value of capacity in M/M/1/C queues
Queueing Systems. 2016. Vol. 83, num. 1-2, p. 157 – 179. DOI : 10.1007/s11134-016-9480-3.Exact simulation of max-stable processes
Biometrika. 2016. Vol. 103, num. 2, p. 303 – 317. DOI : 10.1093/biomet/asw008.Bayesian uncertainty management in temporal dependence of extremes
Extremes. 2016. Vol. 19, num. 3, p. 491 – 515. DOI : 10.1007/s10687-016-0258-0.ODE parameter estimation through a runner’s model application
2016.A characterization of the normal distribution using stationary max-stable processes
Extremes. 2016. Vol. 19, num. 1, p. 1 – 6. DOI : 10.1007/s10687-015-0235-z.Bayesian Inference For The Brown-Resnick Process, With An Application To Extreme Low Temperatures
Annals of Applied Statistics. 2016. Vol. 10, num. 4, p. 2303 – 2324. DOI : 10.1214/16-Aoas980.Likelihood estimators for multivariate extremes
Extremes. 2016. Vol. 19, num. 1, p. 79 – 103. DOI : 10.1007/s10687-015-0230-4.A Levy-derived process seen from its supremum and max-stable processes
Electronic Journal Of Probability. 2016. Vol. 21, p. 14. DOI : 10.1214/16-Ejp1112.2015
Meta-analysis of incomplete microarray studies
Biostatistics. 2015. Vol. 16, num. 4, p. 686 – 700. DOI : 10.1093/biostatistics/kxv014.Likelihood Estimation for the INAR(p) Model by Saddlepoint Approximation
Journal Of The American Statistical Association. 2015. Vol. 110, num. 511, p. 1229 – 1238. DOI : 10.1080/01621459.2014.983230.Statistics of Extremes
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
Stochastic Processes And Their Applications. 2015. Vol. 125, num. 2, p. 780 – 796. DOI : 10.1016/j.spa.2014.09.006.Max-stable processes and stationary systems of Levy particles
Stochastic Processes And Their Applications. 2015. Vol. 125, num. 11, p. 4272 – 4299. DOI : 10.1016/j.spa.2015.07.001.A simple model-based approach to variable selection in classification and clustering
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
2015
2014
Accurate Directional Inference for Vector Parameters in Linear Exponential Families
Journal Of The American Statistical Association. 2014. Vol. 109, num. 505, p. 302 – 314. DOI : 10.1080/01621459.2013.839451.Meta-analysis of Incomplete Microarray Studies
Lausanne, EPFL, 2014.Contributions to Spatial Statistics : Species Distributions and Rare Events
Lausanne, EPFL, 2014.Measuring the relative effect of factors affecting species distribution model predictions
Methods In Ecology And Evolution. 2014. Vol. 5, num. 9, p. 947 – 955. DOI : 10.1111/2041-210X.12203.Additive Smooth Modelling with Splines
2014
Space-time modelling of extreme events
Journal Of The Royal Statistical Society Series B-Statistical Methodology. 2014. Vol. 76, num. 2, p. 439 – 461. DOI : 10.1111/rssb.12035.Efficient inference for spatial extreme value processes associated to log-Gaussian random functions
Biometrika. 2014. Vol. 101, num. 1, p. 1 – 15. DOI : 10.1093/biomet/ast042.Spectral Density Ratio Models for Multivariate Extremes
Journal Of The American Statistical Association. 2014. Vol. 109, num. 506, p. 764 – 776. DOI : 10.1080/01621459.2013.872651.Heavy-tail Phenomena: Spatio-temporal Extremal Dependence
2014
2013
From pointwise testing to a regional vision: An integrated statistical approach to detect nonstationarity in extreme daily rainfall. Application to the Sahelian region
Journal of Geophysical Research: Atmospheres. 2013. Vol. 118, num. 15, p. 8222 – 8237. DOI : 10.1002/jgrd.50340.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
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
Communications in Statistics – Theory and Methods. 2013. Vol. 42, num. 7, p. 1176 – 1192. DOI : 10.1080/03610926.2012.709905.Threshold modeling of extreme spatial rainfall
Water Resources Research. 2013. Vol. 49, num. 8, p. 4633 – 4644. DOI : 10.1002/wrcr.20329.Bayesian Semiparametrics for Modelling the Clustering of Extreme Values
2013.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
Atmospheric Chemistry And Physics. 2013. Vol. 13, num. 1, p. 147 – 164. DOI : 10.5194/acp-13-147-2013.Statistical Modeling and Inference for Spatio-Temporal Extremes
Lausanne, EPFL, 2013.Composite likelihood estimation for the Brown–Resnick process
Biometrika. 2013. Vol. 100, num. 2, p. 511 – 518. DOI : 10.1093/biomet/ass089.Geostatistics of Dependent and Asymptotically Independent Extremes
Mathematical Geosciences. 2013. Vol. 45, num. 5, p. 511 – 529. DOI : 10.1007/s11004-013-9469-y.Spectral modeling of time series with missing data
Applied Mathematical Modelling. 2013. Vol. 37, num. 7, p. 4676 – 4684. DOI : 10.1016/j.apm.2012.09.040.A new representation for multivariate tail probabilities
Bernoulli. 2013. Vol. 19, num. 5B, p. 2689 – 2714. DOI : 10.3150/12-Bej471.Nonstationary Positive Definite Tapering On The Plane
Journal Of Computational And Graphical Statistics. 2013. Vol. 22, num. 4, p. 848 – 865. DOI : 10.1080/10618600.2012.729982.2012
Bivariate Extreme Statistics, Ii
Revstat-Statistical Journal. 2012. Vol. 10, p. 83 – 107.A case study of a “Dragon-King”: The 1999 Venezuelan catastrophe
European Physical Journal-Special Topics. 2012. Vol. 205, p. 131 – 146. DOI : 10.1140/epjst/e2012-01566-6.High-Dimensional Bayesian Clustering with Variable Selection: The R Package bclust
Journal Of Statistical Software. 2012. Vol. 47, p. 1 – 22. DOI : 10.18637/jss.v047.i05.Extreme rainfall in West Africa: A regional modeling
Water Resources Research. 2012. Vol. 48, num. 8, p. W08501. DOI : 10.1029/2012Wr012052.Open Support Platform for Environmental Research (OSPER)-tools for the discovery and exploitation of environmental data
2012. AGU Fall Meeting.Diabetes imaging — quantitative assessment of islets of Langerhans distribution in murine pancreas using extended-focus optical coherence microscopy
Biomedical Optics Express. 2012. Vol. 3, num. 6, p. 1365 – . DOI : 10.1364/BOE.3.001365.Statistical Analysis of Mountain Permafrost Temperatures
Lausanne, EPFL, 2012.Long-term changes in annual maximum snow depth and snowfall in Switzerland based on extreme value statistics
Climatic Change. 2012. Vol. 111, p. 705 – 721. DOI : 10.1007/s10584-011-0159-9.Serum antiglycan antibody detection of nonmucinous ovarian cancers by using a printed glycan array
International Journal Of Cancer. 2012. Vol. 130, p. 138 – 146. DOI : 10.1002/ijc.26002.Geostatistics of extremes
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.Modelling Time Series Extremes
Revstat-Statistical Journal. 2012. Vol. 10, p. 109 – 133.Bayesian inference from composite likelihoods, with an application to spatial extremes
Statistica Sinica. 2012. Vol. 22, num. 2, p. 813 – 845. DOI : 10.5705/ss.2009.248.Anti-glycan antibodies in epithelial ovarian cancer
2012. p. S29 – S29.Digging out the PPP hypothesis: an integrated empirical coverage
Empirical Economics. 2012. Vol. 42, p. 713 – 744. DOI : 10.1007/s00181-010-0441-0.A generalization of the Solis-Wets method
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
Economics Letters. 2012. Vol. 114, p. 32 – 35. DOI : 10.1016/j.econlet.2011.09.007.Statistical modelling of ground temperature in mountain permafrost
Proceedings Of The Royal Society A-Mathematical Physical And Engineering Sciences. 2012. Vol. 468, p. 1472 – 1495. DOI : 10.1098/rspa.2011.0615.Statistical Modeling of Spatial Extremes
Statistical Science. 2012. Vol. 27, p. 161 – 186. DOI : 10.1214/11-STS376.A dimension reduction technique for estimation in linear mixed models
2012. Conference of the LinStat, Tomar, PORTUGAL, Jul 27-31, 2010. p. 219 – 226. DOI : 10.1080/00949655.2011.604032.Extremes: spatial parametric modeling
Encyclopedia of Environmetrics Second Edition; Chichester, UK: John Wiley, 2012. p. 984 – 990.From sensor networks to connected analysis tools
2012. European Geosciences Union General Assembly 2012, Vienna, Austria, April 22-27, 2012.2011
Hierarchical wavelet modelling of environmental sensor data
Brazilian Journal of Probability and Statistics. 2011. Vol. 25, p. 406 – 420. DOI : 10.1214/11-BJPS154.Extreme temperature analysis under forest cover compared to an open field
Agricultural And Forest Meteorology. 2011. Vol. 151, p. 992 – 1001. DOI : 10.1016/j.agrformet.2011.03.005.Comparison of Models for Olfactometer Data
Journal of Agricultural, Biological, and Environmental Statistics. 2011. Vol. 16, num. 2, p. 157 – 169. DOI : 10.1007/s13253-010-0042-6.Statistics of extremes
International Encyclopedia of Statistical Science; new York: Springer, 2011. p. 1484 – .No benefit from combining HE4 and CA125 as ovarian tumor markers in a clinical setting
Gynecologic Oncology. 2011. Vol. 121, p. 487 – 491. DOI : 10.1016/j.ygyno.2011.02.022.Spatial modelling of extreme snow depth
Annals of Applied Statistics. 2011. Vol. 5, p. 1699 – 1725. DOI : 10.1214/11-AOAS464.SpaCEM(3): a software for biological module detection when data is incomplete, high dimensional and dependent
Bioinformatics. 2011. Vol. 27, p. 881 – 882. DOI : 10.1093/bioinformatics/btr034.Discussion of `Threshold modelling of spatially dependent non-stationary extremes with application to hurricane-induced wave heights’ by P. J. Northrop and P. Jonathan
Environmetrics. 2011. Vol. 22, p. 810 – 812. DOI : 10.1002/env.1125.Discussion of the papers by Dankers and Feyen, Cooley, and Keef
2011. International Statistical Institute, Dublin, Ireland, August 21-26, 2011.Comparison of printed glycan array, suspension array and ELISA in the detection of human anti-glycan antibodies
Glycoconjugate Journal. 2011. Vol. 28, p. 507 – 517. DOI : 10.1007/s10719-011-9349-y.2010
Effects of Rewarding and Unrewarding Experiences on the Response to Host-induced Plant Odors of the Generalist Parasitoid Cotesia marginiventris (Hymenoptera: Braconidae)
Journal of Insect Behavior. 2010. Vol. 23, num. 4, p. 303 – 318. DOI : 10.1007/s10905-010-9215-y.Relationship between high daily erythemal UV doses, total ozone, surface albedo and cloudiness: An analysis of 30 years of data from Switzerland and Austria
Atmospheric Research. 2010. Vol. 98, p. 9 – 20. DOI : 10.1016/j.atmosres.2010.03.006.Likelihood-Based Inference for Max-Stable Processes
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
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
Journal of Fuel Cells Science and Technology. 2010. Vol. 7, num. 5, p. 051011. DOI : 10.1115/1.4001019.Comparison of Meta-analysis to Combined Analysis of a Replicated Microarray Study
Meta-analysis and Combining Information in Genetics; Chapman&Hall/CRC, 2010. p. 135 – 156.Extreme events in total ozone over Arosa—Part 2: Fingerprints of atmospheric dynamics and chemistry and effects on mean values and long-term changes
Atmospheric Chemistry And Physics. 2010. Vol. 10, p. 10033 – 10045. DOI : 10.5194/acp-10-10033-2010.Geostatistics of Extremes : A Composite Likelihood Approach
Lausanne, EPFL, 2010.Mapping snow depth return levels: smooth spatial modeling versus station interpolation
Hydrology and Earth System Sciences. 2010. Vol. 14, num. 12, p. 2527 – 2544. DOI : 10.5194/hess-14-2527-2010.Extreme events in total ozone over Arosa—Part 1: Application of extreme value theory
Atmospheric Chemistry And Physics. 2010. Vol. 10, p. 10021 – 10031. DOI : 10.5194/acp-10-10021-2010.The MicroArray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models
Nature Biotechnology. 2010. Vol. 28, p. 827 – U109. DOI : 10.1038/nbt.1665.Three Examples of Accurate Likelihood Inference
American Statistician. 2010. Vol. 64, p. 131 – 139. DOI : 10.1198/tast.2010.09004.Revisiting the Edge, Ten Years On
Communications In Statistics-Theory And Methods. 2010. Vol. 39, p. 1674 – 1688. DOI : 10.1080/03610920902822670.Model misspecification in peaks over threshold analysis
The Annals of Applied Statistics. 2010. Vol. 4, num. 1, p. 203 – 221. DOI : 10.1214/09-AOAS292.2009
Global sensitivity analysis of computer models with functional inputs
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
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
Extremes. 2009. Vol. 12, p. 211 – 218. DOI : 10.1007/s10687-008-0076-0.Statistical analysis of clusters of extreme events
Lausanne, EPFL, 2009.Fast high-dimensional Bayesian classification and clustering
Lausanne, EPFL, 2009.The radial plot in meta-analysis: approximations and applications
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
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
Biometrika. 2009. Vol. 96, p. 479 – 486. DOI : 10.1093/biomet/asp022.Stochastic modelling of prey depletion processes
Journal of Theoretical Biology. 2009. Vol. 259, p. 523 – 532. DOI : 10.1016/j.jtbi.2009.04.017.2008
Some challenges for statistics
Statistical Methods and Applications. 2008. Vol. 17, p. 167 – 181. DOI : 10.1007/s10260-007-0079-z.The Banff challenge: Statistical detection of a noisy signal
Statistical Science. 2008. Vol. 23, num. 3, p. 354 – 364. DOI : 10.1214/08-STS260.A Consistent Confidence Interval for Fuzzy Capability Index
Applied and Computational Mathematics. 2008. Vol. 7, num. 1, p. 119 – 125.Statistical methods for insect choice experiments
Lausanne, EPFL, 2008.A tutorial on adaptive MCMC
Statistics And Computing. 2008. Vol. 18, p. 343 – 373. DOI : 10.1007/s11222-008-9110-y.Entrainment and motion of coarse particles in a shallow water stream down a steep slope
Journal of Fluid Mechanics. 2008. Vol. 595, p. 83 – 114. DOI : 10.1017/S0022112007008774.Quality Assessment for Short Oligonucleotide Microarray Data: Comment
Technometrics. 2008. Vol. 50, p. 276 – 279. DOI : 10.1198/004017008000000370.Accurate parametric inference for small samples
Statistical Science. 2008. Vol. 23, num. 4, p. 465 – 484. DOI : 10.1214/08-STS273.2007
Likelihood estimation of the extremal index
Extreme-Value Analysis, Bern, Switzerland, 23-27 July 2007.Statistical inference for olfactometer data
Applied Statistics. 2007. Vol. 56, p. 479 – 492. DOI : 10.1111/j.1467-9876.2007.00588.x.Applied Asymptotics: Case Studies in Small-Sample Statistics
Cambridge: Cambridge University Press, 2007.Likelihood estimation of the extremal index
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
Ecological Entomology. 2007. Vol. 32, p. 62 – 69. DOI : 10.1111/j.1365-2311.2006.00842.x.Likelihood estimation of the extremal index
Extremes. 2007. Vol. 10, num. 1-2, p. 41 – 55. DOI : 10.1007/s10687-007-0034-2.An Intorduction to the Interface Between C and R
2007
Resamping variance estimation in surveys with missing data
Journal of Offical Statistics. 2007. Vol. 23, p. 371 – 386.Some Basic Functions for Tree Representations of Bayesian Markov Chain Monte Carlo Clustering
2007
Hierarchical wavelet modelling of environmental sensor data
2007
A mixture model for multivariate extremes
Journal of the Royal Statistical Society, series B. 2007. Vol. 69, p. 217 – 229. DOI : 10.1111/j.1467-9868.2007.00585.x.Rapid Classification of Phenotypic Mutants of Arabidopsis via Metabolite Fingerprinting
Plant Physiology. 2007. Vol. 143, p. 1484 – 1492. DOI : 10.1104/pp.106.090795.Reliable confidence intervals in quantitative genetics: Narrow-sense heritability
Theoretical and Applied Genetics. 2007. Vol. 115, p. 933 – 944. DOI : 10.1007/s00122-007-0619-9.2006
Survival and Censored Data
2006
Improved likelihood inference for discrete data
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
Biostatistics. 2006. Vol. 7, num. 4, p. 630 – 641. DOI : 10.1093/biostatistics/kxj032.Clustering of extreme temperatures from 1772 to 2004
Global Change Day 2006, Bern, Switzerland, 2006-04-20.Bootstrap diagnostics and remedies
Canadian Journal of Statistics. 2006. Vol. 34, p. 5 – 27. DOI : 10.1002/cjs.5550340103.Partition resampling and extrapolation averaging: approximation methods for quantifying gene expression in large numbers of short oligonucleotide arrays
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
Pain. 2006. Vol. 122, num. 1-2, p. 14e1 – 14.e14. DOI : 10.1016/j.pain.2005.10.036.Bayesian forecasting of grape moth emergence
Ecological Modelling. 2006. Vol. 197, p. 478 – 489. DOI : 10.1016/j.ecolmodel.2006.03.030.Méthodes de rééchantillonnage pour l’estimation de variance
Journal de la Société Française de Statistique. 2006. Vol. 147, num. 3, p. 3 – 32.Bayesian risk analysis of financial time series
Lausanne, EPFL, 2006.A comparison of naive and conditioned responses of three generalist endoparasitoids of lepidopteran larvae to host-induced plant odours
Animal Biology. 2006. Vol. 56, p. 205 – 220. DOI : 10.1163/157075606777304177.2005
Bootstrap Inference
Encyclopedia of Statistics in Behavioral Science; wiley, 2005. p. 1 – 8.Identification of molecular apocrine breast tumours by microarray analysis
Oncogene. 2005. Vol. 24, num. 29, p. 4660 – 71. DOI : 10.1038/sj.onc.1208561.Saddlepoint approximations to studentized bootstrap distributions based on M-estimates
Computational Statistics. 2005. Vol. 20, num. 2, p. 231 – 244. DOI : 10.1007/BF02789701.The evaluation of evidence in the forensic investigation of fire incidents (Part II): Practical examples of the use of Bayesian networks
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
Journal of Applied Statistics. 2005. Vol. 32, num. 5, p. 443 – 460. DOI : 10.1080/02664760500079340.Generalized additive models for sample extremes
Applied Statistics. 2005. Vol. 54, p. 207 – 222. DOI : 10.1111/j.1467-9876.2005.00479.x.Bootstrap methods
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
Laboratory Investigation. 2005. Vol. 85, p. 1040 – 1050. DOI : 10.1038/labinvest.3700303.A point process approach to value-at-risk estimation
Quantitative Finance. 2005. Vol. 5, num. 2, p. 227 – 234. DOI : 10.1080/14697680500039613.Celebrating Statistics: Papers in Honour of Sir David Cox on the Occasion of his 80th Birthday
Oxford, UK: Oxford University Press, 2005.Generalized monotone additive latent variable models
2005