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Editions published in Journal of the Royal Statistical Society Series B: Statistical Methodology 200
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A quantitative Heppes theorem and multivariate Bernoulli distributions
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Bayesian Pyramids: identifiable multilayer discrete latent structure models for discrete data
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Universal prediction band via semi‐definite programming
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Authors' reply to the Discussion of ‘Assumption‐lean inference for generalised linear model parameters’ by Vansteelandt and Dukes
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Niwen Zhou and Xu Guo’s contribution to the Discussion of ‘Assumption‐lean inference for generalised linear model parameters’ by Vansteelandt and Dukes
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Jiwei Zhao’s contribution to the Discussion of ‘Assumption‐lean inference for generalised linear model parameters’ by Vansteelandt and Dukes
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Eric J Tchetgen Tchetgen’s contribution to the Discussion of ‘Assumption‐lean inference for generalised linear model parameters’ by Vansteelandt and Dukes
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Yanbo Tang's contribution to the Discussion of ‘Assumption‐lean inference for generalised linear model parameters’ by Vansteelandt and Dukes
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Ilya Shpitser’s contribution to the Discussion of ‘Assumption‐lean inference for generalised linear model parameters’ by Vansteelandt and Dukes
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Thomas S. Richardson’s contribution to the Discussion of ‘Assumption‐lean inference for generalised linear model parameters’ by Vansteelandt and Dukes
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Rachael V. Phillips and Mark J. van der Laan’s contribution to the Discussion of ‘Assumption‐lean inference for generalised linear model parameters’ by Vansteelandt and Dukes
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Elizabeth L Ogburn, Junhui Cai, Arun K Kuchibhotla, Richard A Berk and Andreas Buja’s contribution to the Discussion of ‘Assumption‐lean inference for generalised linear model parameters’ by Vansteelandt and Dukes
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Kuldeep Kumar’s contribution to the Discussion of ‘Assumption‐lean inference for generalised linear model parameters’ by Vansteelandt and Dukes
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Michael Lavine and James Hodges’ contribution to the Discussion of ‘Assumption‐lean inference for generalised linear model parameters’ by Vansteelandt and Dukes
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Ian Hunt's contribution to the Discussion of ‘Assumption‐lean inference for generalised linear model parameters’ by Vansteelandt and Dukes
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Oliver Hines and Karla Diaz‐Ordazʼs contribution to the discussion of ‘Assumption‐lean inference for generalised linear model parameters’ by Vansteelandt and Dukes
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Chaohua Dong, Jiti Gao and Oliver Linton’s contribution to the Discussion of ‘Assumption‐lean inference for generalised linear model parameters’ by Vansteelandt and Dukes
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Anna Choi and Weng Kee Wong’s contribution to the Discussion of ‘Assumption‐lean inference for generalised linear model parameters’ by Vansteelandt and Dukes
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Andreas Buja, Richard A. Berk, Arun K. Kuchibhotla, Linda Zhao and Ed George’s contribution to the Discussion of ‘Assumption‐lean inference for generalised linear model parameters’ by Vansteelandt and Dukes
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Blair Bilodeau's contribution to the Discussion of ‘Assumption‐lean inference for generalised linear model parameters’ by Vansteelandt and Dukes
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Pallavi Basuʼs contribution to the Discussion of ‘Assumption‐lean inference for generalised linear model parameters’ by Vansteelandt and Dukes
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Heather Battey’s contribution to the Discussion of ‘Assumption‐lean inference for generalised linear model parameters’ by Vansteelandt and Dukes
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Christian Hennig's contribution to the Discussion of ‘Assumption‐lean inference for generalised linear model parameters’ by Vansteelandt and Dukes
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Mats J Stensrud and Aaron L. Sarvet’s contribution to the Discussion of ‘Assumption‐lean inference for generalised linear model parameters’ by Vansteelandt and Dukes
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Peng Ding’s contribution to the Discussion of ‘Assumption‐lean inference for generalised linear model parameters’ by Vansteelandt and Dukes
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Seconder of the vote of thanks to Vansteelandt and Dukes and contribution to the Discussion of ‘Assumption‐lean inference for generalised linear model parameters’
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Proposer of the vote of thanks and contribution to the Discussion of ‘Assumption‐lean inference for generalised linear model parameters’ by Vansteelandt and Dukes
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Assumption‐lean inference for generalised linear model parameters
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Optimal Thinning of MCMC Output
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Transfer learning for high‐dimensional linear regression: Prediction, estimation and minimax optimality
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Approximate Laplace approximations for scalable model selection
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Smoothing splines on Riemannian manifolds, with applications to 3D shape space
Subject - wd:Q15759195