Wicher P Bergsma

发表

Efficient and Interpretable Additive Gaussian Process Regression and Application to Analysis of Hourly-recorded $\text{NO}_2$ Concentrations in London

Sahoko Ishida, Wicher P Bergsma, 2023, 2305.07073.

Regression modelling with I-priors

Wicher Bergsma, Haziq Jamil, Wicher P Bergsma, 2020 .

Efficient Additive Gaussian Process Regression for Large-scale Data and Application to Analysis of Hourly-recorded NO$_2$ Concentrations in London (preprint)

Sahoko Ishida, Wicher P Bergsma, 2023 .

On a New Correlation Coefficient, its Orthogonal Decomoposition, and Associated Tests of Independence

Wicher P. Bergsma, Wicher Bergsma, Wicher P Bergsma, 2005, math/0604627.

ST ] 2 8 A pr 2 00 6 ON A NEW CORRELATION COEFFICIENT , ITS ORTHOGONAL DECOMPOSITION AND ASSOCIATED TESTS OF INDEPENDENCE By

Wicher Bergsma, Wicher P Bergsma, 2020 .

Double Generative Adversarial Networks for Conditional Independence Testing

Wicher P. Bergsma, Wicher Bergsma, Lexin Li, 2020, J. Mach. Learn. Res..

iprior: An R Package for Regression Modelling using I-priors.

Wicher P. Bergsma, Wicher Bergsma, Haziq Jamil, 2019, 1912.01376.

Regression with I-priors

Wicher P. Bergsma, Wicher P Bergsma, 2017, Econometrics and Statistics.

Bayesian Variable Selection for Linear Models Using I-Priors

Wicher Bergsma, Haziq Jamil, Wicher P Bergsma, 2020 .

Additive interaction modelling using I-priors

Wicher Bergsma, Haziq Jamil, Wicher P Bergsma, 2020, 2007.15766.

Case-Base-Control designs

M. Weale, N. S. Elhezzani, Wicher P Bergsma, 2019, bioRxiv.

Estimation for Dynamic and Static Panel Probit Models with Large Individual Effects

Wicher Bergsma, Q. Yao, Wei Gao, 2014, 1409.7776.

Marginal Models: an Overview

Wicher Bergsma, T. Rudas, Wicher P Bergsma, 2023, 2304.03380.

Parameterizations and Fitting of Bi‐directed Graph Models to Categorical Data

Monia Lupparelli, Giovanni M. Marchetti, Wicher P. Bergsma, 2008, 0801.1440.

Marginal models for categorical data

Wicher P. Bergsma, Wicher Bergsma, T. Rudas, 2002 .

Maximum Augmented Empirical Likelihood Estimation of Categorical Marginal Models for Large Sparse Contingency Tables

Wicher P. Bergsma, Letty Koopman, Wicher P Bergsma, 2023, Psychometrika.

Advancements in Marginal Modeling for Categorical Data

Wicher Bergsma, Marcel A. Croon, Jacques A. Hagenaars, 2013 .

Nonloglinear marginal latent class models

Wicher P. Bergsma, J. Hagenaars, Wicher Bergsma, 2019 .

Bayesian Posterior Estimation of Logit Parameters with Small Samples

J. Vermunt, F. Galindo‐Garre, Wicher P Bergsma, 2004 .

Analyzing Change in Categorical Variables by Generalized Log-Linear Models

J. Hagenaars, Wicher Bergsma, M. Croon, 2000 .

A bias-correction for Cramér’s and Tschuprow’s

Wicher Bergsma, Wicher Bergsma, Wicher P Bergsma, 2013 .

A note on the distribution of the partial correlation coefficient with nonparametrically estimated marginal regressions

Wicher P Bergsma, 2011, 1101.4616.

Nonparametric Testing of Conditional Independence by Means of the Partial Copula

Wicher P. Bergsma, Wicher Bergsma, Wicher P Bergsma, 2010, 1101.4607.

Testing conditional independence for continuous random variables

Wicher P. Bergsma, Wicher Bergsma, Wicher P Bergsma, 2004 .

A Kernel Test for Three-Variable Interactions

Arthur Gretton, Dino Sejdinovic, Wicher Bergsma, 2013, NIPS.

A consistent test of independence based on a sign covariance related to Kendall's tau

Wicher P. Bergsma, Wicher Bergsma, A. Dassios, 2010, 1007.4259.

Polytomous Latent Scales for the Investigation of the Ordering of Items

Klaas Sijtsma, Wicher Bergsma, L. Andries van der Ark, 2011 .

Modeling conditional and marginal association in contingency tables

T. Rudas, Wicher P Bergsma, 2002 .

Conditional and marginal association in contingency tables

Wicher Bergsma, T. Rudas, Wicher P Bergsma, 2002 .

Bayesian causal inference for count potential outcomes

Young Lee, Wicher P. Bergsma, Marie-Abele C. Bind, 2020, 2008.03271.