Works matching IS 00063444 AND DT 2018 AND VI 105 AND IP 3
Results: 18
Variance estimation in the particle filter.
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- Biometrika, 2018, v. 105, n. 3, p. 609, doi. 10.1093/biomet/asy028
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Targeted learning ensembles for optimal individualized treatment rules with time-to-event outcomes.
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- Biometrika, 2018, v. 105, n. 3, p. 723, doi. 10.1093/biomet/asy017
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When is the first spurious variable selected by sequential regression procedures?
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- Biometrika, 2018, v. 105, n. 3, p. 517, doi. 10.1093/biomet/asy032
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Symmetric rank covariances: a generalized framework for nonparametric measures of dependence.
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- Biometrika, 2018, v. 105, n. 3, p. 547, doi. 10.1093/biomet/asy021
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A structural break test for extremal dependence in β-mixing random vectors.
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- Biometrika, 2018, v. 105, n. 3, p. 627, doi. 10.1093/biomet/asy030
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Shrinking characteristics of precision matrix estimators.
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- Biometrika, 2018, v. 105, n. 3, p. 563, doi. 10.1093/biomet/asy023
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Sequential rerandomization.
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- Biometrika, 2018, v. 105, n. 3, p. 745, doi. 10.1093/biomet/asy031
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A semiparametric extension of the stochastic block model for longitudinal networks.
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- Biometrika, 2018, v. 105, n. 3, p. 665, doi. 10.1093/biomet/asy016
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On Bayes factors for the linear model.
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- Biometrika, 2018, v. 105, n. 3, p. 739, doi. 10.1093/biomet/asy022
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Local polynomial regression with correlated errors in random design and unknown correlation structure.
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- Biometrika, 2018, v. 105, n. 3, p. 681, doi. 10.1093/biomet/asy025
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High-dimensional peaks-over-threshold inference.
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- Biometrika, 2018, v. 105, n. 3, p. 575, doi. 10.1093/biomet/asy026
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Covariate association eliminating weights: a unified weighting framework for causal effect estimation.
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- Biometrika, 2018, v. 105, n. 3, p. 709, doi. 10.1093/biomet/asy015
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Bayesian spatial monotonic multiple regression.
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- Biometrika, 2018, v. 105, n. 3, p. 691, doi. 10.1093/biomet/asy019
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Asymptotic properties of approximate Bayesian computation.
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- Biometrika, 2018, v. 105, n. 3, p. 593, doi. 10.1093/biomet/asy027
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Asymptotic post-selection inference for the Akaike information criterion.
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- Biometrika, 2018, v. 105, n. 3, p. 645, doi. 10.1093/biomet/asy018
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Asymptotic normality of interpoint distances for high-dimensional data with applications to the two-sample problem.
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- Biometrika, 2018, v. 105, n. 3, p. 529, doi. 10.1093/biomet/asy020
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Assessing replicability of findings across two studies of multiple features.
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- Biometrika, 2018, v. 105, n. 3, p. 505, doi. 10.1093/biomet/asy029
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Amendments and Corrections‘Information-theoretic optimality of observation-driven time series models for continuous responses’.
- Published in:
- Biometrika, 2018, v. 105, n. 3, p. 753, doi. 10.1093/biomet/asy039
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- Article