Works matching IS 00063444 AND DT 2020 AND VI 107 AND IP 4
Results: 17
Envelopes in multivariate regression models with nonlinearity and heteroscedasticity.
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- Biometrika, 2020, v. 107, n. 4, p. 965, doi. 10.1093/biomet/asaa036
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Extended stochastic gradient Markov chain Monte Carlo for large-scale Bayesian variable selection.
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- Biometrika, 2020, v. 107, n. 4, p. 997, doi. 10.1093/biomet/asaa029
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Inference under unequal probability sampling with the Bayesian exponentially tilted empirical likelihood.
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- Biometrika, 2020, v. 107, n. 4, p. 857, doi. 10.1093/biomet/asaa028
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Combining p-values via averaging.
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- Biometrika, 2020, v. 107, n. 4, p. 791, doi. 10.1093/biomet/asaa027
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A unified approach to the calculation of information operators in semiparametric models.
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- Biometrika, 2020, v. 107, n. 4, p. 983, doi. 10.1093/biomet/asaa037
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On testing marginal versus conditional independence.
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- Biometrika, 2020, v. 107, n. 4, p. 771, doi. 10.1093/biomet/asaa040
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On specification tests for composite likelihood inference.
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- Biometrika, 2020, v. 107, n. 4, p. 907, doi. 10.1093/biomet/asaa039
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Regression-adjusted average treatment effect estimates in stratified randomized experiments.
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- Biometrika, 2020, v. 107, n. 4, p. 935, doi. 10.1093/biomet/asaa038
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Efficient posterior sampling for high-dimensional imbalanced logistic regression.
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- Biometrika, 2020, v. 107, n. 4, p. 1005, doi. 10.1093/biomet/asaa035
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General regression model for the subdistribution of a competing risk under left-truncation and right-censoring.
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- Biometrika, 2020, v. 107, n. 4, p. 949, doi. 10.1093/biomet/asaa034
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A conditional test with demonstrated insensitivity to unmeasured bias in matched observational studies.
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- Biometrika, 2020, v. 107, n. 4, p. 827, doi. 10.1093/biomet/asaa032
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Classification via local manifold approximation.
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- Biometrika, 2020, v. 107, n. 4, p. 1013, doi. 10.1093/biomet/asaa033
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The Pitman–Yor multinomial process for mixture modelling.
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- Biometrika, 2020, v. 107, n. 4, p. 891, doi. 10.1093/biomet/asaa030
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Optimal Bayesian estimation for random dot product graphs.
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- Biometrika, 2020, v. 107, n. 4, p. 875, doi. 10.1093/biomet/asaa031
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Demystifying a class of multiply robust estimators.
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- Biometrika, 2020, v. 107, n. 4, p. 919, doi. 10.1093/biomet/asaa026
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Estimation in linear errors-in-variables models with unknown error distribution.
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- Biometrika, 2020, v. 107, n. 4, p. 841, doi. 10.1093/biomet/asaa025
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Multivariate one-sided testing in matched observational studies as an adversarial game.
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- Biometrika, 2020, v. 107, n. 4, p. 809, doi. 10.1093/biomet/asaa024
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