William H. Aeberhard
William H. Aeberhard
Department of Mathematical Sciences, Stevens Institute of Technology
Verified email at stevens.edu
TitleCited byYear
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
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
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
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
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
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, 2018
State-Space Models for Improved Predictions in Fisheries Management
W Aeberhard
2017 AAAS Annual Meeting (February 16-20, 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
Contributions to overdispersed count data modeling: robustness, small samples and other extensions
W Aeberhard
University of Geneva, 2015
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
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Articles 1–10