Works matching IS 00063444 AND DT 2019 AND VI 106 AND IP 4
Results: 18
Sequentially additive nonignorable missing data modelling using auxiliary marginal information.
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- Biometrika, 2019, v. 106, n. 4, p. 889, doi. 10.1093/biomet/asz054
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Fréchet analysis of variance for random objects.
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- Biometrika, 2019, v. 106, n. 4, p. 803, doi. 10.1093/biomet/asz052
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On causal discovery with an equal-variance assumption.
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- Biometrika, 2019, v. 106, n. 4, p. 973, doi. 10.1093/biomet/asz049
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Causal inference with confounders missing not at random.
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- Biometrika, 2019, v. 106, n. 4, p. 875, doi. 10.1093/biomet/asz048
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Testing for arbitrary interference on experimentation platforms.
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- Biometrika, 2019, v. 106, n. 4, p. 929, doi. 10.1093/biomet/asz047
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Fast exact conformalization of the lasso using piecewise linear homotopy.
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- Biometrika, 2019, v. 106, n. 4, p. 749, doi. 10.1093/biomet/asz046
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Network dependence testing via diffusion maps and distance-based correlations.
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- Biometrika, 2019, v. 106, n. 4, p. 857, doi. 10.1093/biomet/asz045
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Column-orthogonal strong orthogonal arrays of strength two plus and three minus.
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- Biometrika, 2019, v. 106, n. 4, p. 997, doi. 10.1093/biomet/asz043
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Semiparametric segment M-estimation for locally stationary diffusions.
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- Biometrika, 2019, v. 106, n. 4, p. 941, doi. 10.1093/biomet/asz042
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Simultaneous control of all false discovery proportions in large-scale multiple hypothesis testing.
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- Biometrika, 2019, v. 106, n. 4, p. 841, doi. 10.1093/biomet/asz041
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Conjugate Bayes for probit regression via unified skew-normal distributions.
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- Biometrika, 2019, v. 106, n. 4, p. 765, doi. 10.1093/biomet/asz034
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Tyler shape depth.
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- Biometrika, 2019, v. 106, n. 4, p. 913, doi. 10.1093/biomet/asz039
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On nonparametric maximum likelihood estimation with double truncation.
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- Biometrika, 2019, v. 106, n. 4, p. 989, doi. 10.1093/biomet/asz038
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Accounting for unobserved covariates with varying degrees of estimability in high-dimensional biological data.
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- Biometrika, 2019, v. 106, n. 4, p. 823, doi. 10.1093/biomet/asz037
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Within-cluster resampling for multilevel models under informative cluster size.
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- Biometrika, 2019, v. 106, n. 4, p. 965, doi. 10.1093/biomet/asz035
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Bootstrapping spectral statistics in high dimensions.
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- Biometrika, 2019, v. 106, n. 4, p. 781, doi. 10.1093/biomet/asz040
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Bayesian jackknife empirical likelihood.
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- Biometrika, 2019, v. 106, n. 4, p. 981, doi. 10.1093/biomet/asz031
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Distributional consistency of the lasso by perturbation bootstrap.
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- Biometrika, 2019, v. 106, n. 4, p. 957, doi. 10.1093/biomet/asz029
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