Works matching IS 00359254 AND DT 2020 AND VI 69 AND IP 2
Results: 13
Bayesian hierarchical modelling of growth curve derivatives via sequences of quotient differences.
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- Journal of the Royal Statistical Society: Series C (Applied Statistics), 2020, v. 69, n. 2, p. 459, doi. 10.1111/rssc.12399
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A flexible parametric modelling framework for survival analysis.
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- Journal of the Royal Statistical Society: Series C (Applied Statistics), 2020, v. 69, n. 2, p. 429, doi. 10.1111/rssc.12398
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Estimating seal pup production in the Greenland Sea by using Bayesian hierarchical modelling.
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- Journal of the Royal Statistical Society: Series C (Applied Statistics), 2020, v. 69, n. 2, p. 327, doi. 10.1111/rssc.12397
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Using Cox regression to develop linear rank tests with zero‐inflated clustered data.
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- Journal of the Royal Statistical Society: Series C (Applied Statistics), 2020, v. 69, n. 2, p. 393, doi. 10.1111/rssc.12396
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Factor‐augmented Bayesian cointegration models: a case‐study on the soybean crush spread.
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- Journal of the Royal Statistical Society: Series C (Applied Statistics), 2020, v. 69, n. 2, p. 483, doi. 10.1111/rssc.12395
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Bayesian protein sequence and structure alignment.
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- Journal of the Royal Statistical Society: Series C (Applied Statistics), 2020, v. 69, n. 2, p. 301, doi. 10.1111/rssc.12394
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Efficient data augmentation for multivariate probit models with panel data: an application to general practitioner decision making about contraceptives.
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- Journal of the Royal Statistical Society: Series C (Applied Statistics), 2020, v. 69, n. 2, p. 277, doi. 10.1111/rssc.12393
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Assessing heterogeneity in transition propensity in multistate capture–recapture data.
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- Journal of the Royal Statistical Society: Series C (Applied Statistics), 2020, v. 69, n. 2, p. 413, doi. 10.1111/rssc.12392
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Modelling the spatial extent and severity of extreme European windstorms.
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- Journal of the Royal Statistical Society: Series C (Applied Statistics), 2020, v. 69, n. 2, p. 223, doi. 10.1111/rssc.12391
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Modelling environmental DNA data; Bayesian variable selection accounting for false positive and false negative errors.
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- Journal of the Royal Statistical Society: Series C (Applied Statistics), 2020, v. 69, n. 2, p. 377, doi. 10.1111/rssc.12390
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The analysis of transformations for profit‐and‐loss data.
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- Journal of the Royal Statistical Society: Series C (Applied Statistics), 2020, v. 69, n. 2, p. 251, doi. 10.1111/rssc.12389
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Estimation and inference in mixed effect regression models using shape constraints, with application to tree height estimation.
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- Journal of the Royal Statistical Society: Series C (Applied Statistics), 2020, v. 69, n. 2, p. 353, doi. 10.1111/rssc.12388
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- Article
Issue Information.
- Published in:
- Journal of the Royal Statistical Society: Series C (Applied Statistics), 2020, v. 69, n. 2, p. 221, doi. 10.1111/rssc.12359
- Publication type:
- Article