William H. Aeberhard

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Eva CantoniResearch Center for Statistics, Geneva School of Economics and Management, University of GenevaVerified email at unige.ch
Stephane HeritierMonash UniversityVerified email at monash.edu
Sebastien BiassEarth Observatory of SingaporeVerified email at ntu.edu.sg
Costanza BonadonnaProfessor of Physical Volcanology and Geological Risk, University of GenevaVerified email at unige.ch
Boris WormProfessor of Biology, Dalhousie UniversityVerified email at dal.ca
Gholamhossein (Mohsen) bagheriGroup Leader at Max Planck Institute for Dynamics and Self-OrganizationVerified email at ds.mpg.de
Anders NielsenDTU-AquaVerified email at aqua.dtu.dk
Omar DefeoFaculty of Sciences, UruguayVerified email at dinara.gub.uy
Ricardo CardosoProf. Dr. Ecologia, Universidade Federal do Estado do Rio de Janeiro (UNIRIO)Verified email at unirio.br
Leonardo OrtegaDirección Nacional de Recursos AcuáticosVerified email at mgap.gub.uy
Carlos Alberto de Moura BarbozaProfessor Adjunto da Universidade Federal do Rio de JaneiroVerified email at macae.ufrj.br
Francisco Rafael BarbozaEstonian Marine Institute, University of TartuVerified email at ut.ee
Tatiana Medeiros Barbosa CabriniUniversidade Federal do Estado do Rio de JaneiroVerified email at unirio.br
Chris FieldProfessor of Statistics, Dalhousie University, Halifax, CanadaVerified email at mathstat.dal.ca
Giampiero MarraProfessor of Statistics, University College LondonVerified email at ucl.ac.uk
Rosalba RadiceProfessor of StatisticsVerified email at city.ac.uk
Dr. Manuel DureuilPostdoctoral Fellow, Marine Conservation, Dalhousie UniversityVerified email at Dal.Ca
Hans R. KuenschSeminar fur Statistik, Department of Mathematics, ETH ZurichVerified email at stat.math.ethz.ch
ximing xuChildren's Hospital of Chongqing Medical UniversityVerified email at hospital.cqmu.edu.cn

William H. Aeberhard

Swiss Data Science Center, ETH Zurich

Verified email at sdsc.ethz.ch - Homepage

Computational Statistics Ecological Modeling Robust Statistics State Space Models


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Robust inference in the negative binomial regression model with an application to falls data WH Aeberhard, E Cantoni, S Heritier Biometrics 70 (4), 920-931, 2014	51	2014
Review of state-space models for fisheries science WH Aeberhard, J Mills Flemming, A Nielsen Annual Review of Statistics and Its Application 5 (1), 215-235, 2018	50	2018
TError: towards a better quantification of the uncertainty propagated during the characterization of tephra deposits S Biasse, G Bagheri, W Aeberhard, C Bonadonna Statistics in Volcanology 1 (2), 1-27, 2014	27	2014
Aggregate patterns of macrofaunal diversity: An interocean comparison O Defeo, CAM Barboza, FR Barboza, WH Aeberhard, T Cabrini, ... Global Ecology and Biogeography 26 (7), 823-834, 2017	23	2017
Identifiable state‐space models: A case study of the Bay of Fundy sea scallop fishery Y Yin, WH Aeberhard, SJ Smith, J Mills Flemming Canadian Journal of Statistics 47 (1), 27-45, 2019	11	2019
The conditionally autoregressive hidden Markov model (CarHMM): Inferring behavioural states from animal tracking data exhibiting conditional autocorrelation E Lawler, K Whoriskey, WH Aeberhard, C Field, JM Flemming Journal of Agricultural, Biological and Environmental Statistics 24 (4), 651-668, 2019	7	2019
Robust Fitting and Smoothing Parameter Selection for Generalized Additive Models for Location, Scale and Shape WH Aeberhard, E Cantoni, G Marra, R Radice Statistics and Computing 31 (11), 1-16, 2021	5	2021
Saddlepoint tests for accurate and robust inference on overdispersed count data WH Aeberhard, E Cantoni, S Heritier Computational Statistics & Data Analysis 107, 162-175, 2017	5	2017
Unified natural mortality estimation for teleosts and elasmobranchs M Dureuil, WH Aeberhard, KA Burnett, RE Hueter, JP Tyminski, B Worm Marine Ecology Progress Series 667, 113-129, 2021	4	2021
Insights into the vulnerability of vegetation to tephra fallouts from interpretable machine learning and big Earth observation data S Biass, SF Jenkins, WH Aeberhard, P Delmelle, T Wilson Natural Hazards and Earth System Sciences Discussions, 1-55, 2022		2022
Robust estimation for discrete‐time state space models WH Aeberhard, E Cantoni, C Field, HR Künsch, J Mills Flemming, X Xu Scandinavian Journal of Statistics 48 (4), 1127-1147, 2021		2021
Workshop on the review and future of state space stock assessment models in ICES (WKRFSAM) A Nielsen, A Perreault, CW Berg, C Albertsen, C Minto, C Millar, ... Workshop on the review and future of state space stock assessment models in ICES, 2020		2020
Comparison of robust saddlepoint tests: the negative binomial regression case S Heritier, W Aeberhard, E Cantoni Book of Abstracts, 21, 2017		2017
State-Space Models for Improved Predictions in Fisheries Management W Aeberhard 2017 AAAS Annual Meeting (February 16-20, 2017), 2017		2017
Le modèle linéaire généralisé (GLM) robuste W Aeberhard, E Cantoni Méthodes robustes en statistique, Ed. by J.-J. Droesbeke, G. Saporta, and C …, 2015		2015
Contributions to overdispersed count data modeling: robustness, small samples and other extensions W Aeberhard University of Geneva, 2015		2015
TError S Biass, G Bagheri, W Aeberhard, C Bonadonna		2014
Power and Sample Size Calculation in a Negative Binomial Regression Framework: The Power of Falls: Might the" Holy Trinity" Help? W Aeberhard University of Geneva, 2010		2010
Web-based Supporting Material for Robust Fitting and Smoothing Parameter Selection for Generalized Additive Models for Location, Scale and Shape WH Aeberhard, E Cantoni, G Marra, R Radice

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