Works matching IS 00359254 AND DT 2019 AND VI 68 AND IP 4
Results: 18
A computationally efficient correlated mixed probit model for credit risk inference.
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- Journal of the Royal Statistical Society: Series C (Applied Statistics), 2019, v. 68, n. 4, p. 1183, doi. 10.1111/rssc.12352
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Joint modelling of competing risks and current status data: an application to a spontaneous labour study.
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- Journal of the Royal Statistical Society: Series C (Applied Statistics), 2019, v. 68, n. 4, p. 1167, doi. 10.1111/rssc.12351
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The mean, variance and correlation for bivariate recurrent event data with a terminal event.
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- Journal of the Royal Statistical Society: Series C (Applied Statistics), 2019, v. 68, n. 4, p. 1029, doi. 10.1111/rssc.12350
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Non‐parametric overdose control for dose finding in drug combination trials.
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- Journal of the Royal Statistical Society: Series C (Applied Statistics), 2019, v. 68, n. 4, p. 1111, doi. 10.1111/rssc.12349
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Non‐parametric Bayes models for mixed scale longitudinal surveys.
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- Journal of the Royal Statistical Society: Series C (Applied Statistics), 2019, v. 68, n. 4, p. 1091, doi. 10.1111/rssc.12348
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Bayesian inference for stochastic differential equation mixed effects models of a tumour xenography study.
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- Journal of the Royal Statistical Society: Series C (Applied Statistics), 2019, v. 68, n. 4, p. 887, doi. 10.1111/rssc.12347
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Data integrative Bayesian inference for mixtures of regression models.
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- Journal of the Royal Statistical Society: Series C (Applied Statistics), 2019, v. 68, n. 4, p. 941, doi. 10.1111/rssc.12346
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Comparing Kaplan–Meier curves with delayed treatment effects: applications in immunotherapy trials.
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- Journal of the Royal Statistical Society: Series C (Applied Statistics), 2019, v. 68, n. 4, p. 915, doi. 10.1111/rssc.12345
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Markov switching integer‐valued generalized auto‐regressive conditional heteroscedastic models for dengue counts.
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- Journal of the Royal Statistical Society: Series C (Applied Statistics), 2019, v. 68, n. 4, p. 963, doi. 10.1111/rssc.12344
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Detecting anisotropy in fingerprint growth.
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- Journal of the Royal Statistical Society: Series C (Applied Statistics), 2019, v. 68, n. 4, p. 1007, doi. 10.1111/rssc.12343
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Modelling extreme rain accumulation with an application to the 2011 Lake Champlain flood.
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- Journal of the Royal Statistical Society: Series C (Applied Statistics), 2019, v. 68, n. 4, p. 831, doi. 10.1111/rssc.12342
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An instrumental variable procedure for estimating Cox models with non‐proportional hazards in the presence of unmeasured confounding.
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- Journal of the Royal Statistical Society: Series C (Applied Statistics), 2019, v. 68, n. 4, p. 985, doi. 10.1111/rssc.12341
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Estimation of the Von Bertalanffy growth model when ages are measured with error.
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- Journal of the Royal Statistical Society: Series C (Applied Statistics), 2019, v. 68, n. 4, p. 1131, doi. 10.1111/rssc.12340
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Health effects of sanitation facilities: a Bayesian semiparametric analysis of compositional data.
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- Journal of the Royal Statistical Society: Series C (Applied Statistics), 2019, v. 68, n. 4, p. 1149, doi. 10.1111/rssc.12339
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Improving the identification of antigenic sites in the H1N1 influenza virus through accounting for the experimental structure in a sparse hierarchical Bayesian model.
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- Journal of the Royal Statistical Society: Series C (Applied Statistics), 2019, v. 68, n. 4, p. 859, doi. 10.1111/rssc.12338
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Testing critical points of non‐parametric regression curves: application to the management of stalked barnacles.
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- Journal of the Royal Statistical Society: Series C (Applied Statistics), 2019, v. 68, n. 4, p. 1051, doi. 10.1111/rssc.12336
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Additive quantile regression for clustered data with an application to children's physical activity.
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- Journal of the Royal Statistical Society: Series C (Applied Statistics), 2019, v. 68, n. 4, p. 1071, doi. 10.1111/rssc.12333
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Issue Information.
- Published in:
- Journal of the Royal Statistical Society: Series C (Applied Statistics), 2019, v. 68, n. 4, p. 829, doi. 10.1111/rssc.12303
- Publication type:
- Article