Works matching IS 00063444 AND DT 2021 AND VI 108 AND IP 1
Results: 18
Hypothesis testing for phylogenetic composition: a minimum-cost flow perspective.
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- Biometrika, 2021, v. 108, n. 1, p. 17, doi. 10.1093/biomet/asaa061
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The asymptotic distribution of modularity in weighted signed networks.
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- Biometrika, 2021, v. 108, n. 1, p. 1, doi. 10.1093/biomet/asaa059
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Matrix-variate logistic regression with measurement error.
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- Biometrika, 2021, v. 108, n. 1, p. 83, doi. 10.1093/biomet/asaa056
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In search of lost mixing time: adaptive Markov chain Monte Carlo schemes for Bayesian variable selection with very large p.
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- Biometrika, 2021, v. 108, n. 1, p. 53, doi. 10.1093/biomet/asaa055
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Characterization of parameters with a mixed bias property.
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- Biometrika, 2021, v. 108, n. 1, p. 231, doi. 10.1093/biomet/asaa054
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An asymptotic and empirical smoothing parameters selection method for smoothing spline ANOVA models in large samples.
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- Biometrika, 2021, v. 108, n. 1, p. 149, doi. 10.1093/biomet/asaa047
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High-quantile regression for tail-dependent time series.
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- Biometrika, 2021, v. 108, n. 1, p. 113, doi. 10.1093/biomet/asaa046
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Event history analysis of dynamic networks.
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- Biometrika, 2021, v. 108, n. 1, p. 223, doi. 10.1093/biomet/asaa045
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Heterogeneous individual risk modelling of recurrent events.
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- Biometrika, 2021, v. 108, n. 1, p. 183, doi. 10.1093/biomet/asaa053
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High-dimensional empirical likelihood inference.
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- Biometrika, 2021, v. 108, n. 1, p. 127, doi. 10.1093/biomet/asaa051
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A likelihood analysis of quantile-matching transformations.
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- Biometrika, 2021, v. 108, n. 1, p. 247, doi. 10.1093/biomet/asaa048
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Jeffreys-prior penalty, finiteness and shrinkage in binomial-response generalized linear models.
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- Biometrika, 2021, v. 108, n. 1, p. 71, doi. 10.1093/biomet/asaa052
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Testing for measurement error in survey data analysis using paradata.
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- Biometrika, 2021, v. 108, n. 1, p. 239, doi. 10.1093/biomet/asaa050
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Jump or kink: on super-efficiency in segmented linear regression breakpoint estimation.
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- Biometrika, 2021, v. 108, n. 1, p. 215, doi. 10.1093/biomet/asaa049
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Large-sample asymptotics of the pseudo-marginal method.
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- Biometrika, 2021, v. 108, n. 1, p. 37, doi. 10.1093/biomet/asaa044
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Optimal subsampling for quantile regression in big data.
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- Biometrika, 2021, v. 108, n. 1, p. 99, doi. 10.1093/biomet/asaa043
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Modelling temporal biomarkers with semiparametric nonlinear dynamical systems.
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- Biometrika, 2021, v. 108, n. 1, p. 199, doi. 10.1093/biomet/asaa042
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Functional regression on the manifold with contamination.
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- Biometrika, 2021, v. 108, n. 1, p. 167, doi. 10.1093/biomet/asaa041
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