Works matching IS 00359254 AND DT 2024 AND VI 73 AND IP 5
Results: 14
Contents of Volume 73, 2024.
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- Journal of the Royal Statistical Society: Series C (Applied Statistics), 2024, v. 73, n. 5, p. 1411, doi. 10.1093/jrsssc/qlae056
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- Article
A Bayesian valuation framework for catastrophe bonds.
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- Journal of the Royal Statistical Society: Series C (Applied Statistics), 2024, v. 73, n. 5, p. 1389, doi. 10.1093/jrsssc/qlae041
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An adaptive functional regression framework for locally heterogeneous signals in spectroscopy.
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- Journal of the Royal Statistical Society: Series C (Applied Statistics), 2024, v. 73, n. 5, p. 1370, doi. 10.1093/jrsssc/qlae040
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Joint modelling of survival and backwards recurrence outcomes: an analysis of factors associated with fertility treatment in the U.S.
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- Journal of the Royal Statistical Society: Series C (Applied Statistics), 2024, v. 73, n. 5, p. 1355, doi. 10.1093/jrsssc/qlae039
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Non-parametric Bayesian approach to multiple treatment comparisons in network meta-analysis with application to comparisons of anti-depressants.
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- Journal of the Royal Statistical Society: Series C (Applied Statistics), 2024, v. 73, n. 5, p. 1333, doi. 10.1093/jrsssc/qlae038
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A semi-parametric maximum-likelihood analysis of measurement error in population size estimation.
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- Journal of the Royal Statistical Society: Series C (Applied Statistics), 2024, v. 73, n. 5, p. 1310, doi. 10.1093/jrsssc/qlae037
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A novel CFA + EFA model to detect aberrant respondents.
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- Journal of the Royal Statistical Society: Series C (Applied Statistics), 2024, v. 73, n. 5, p. 1283, doi. 10.1093/jrsssc/qlae036
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A state-space perspective on modelling and inference for online skill rating.
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- Journal of the Royal Statistical Society: Series C (Applied Statistics), 2024, v. 73, n. 5, p. 1262, doi. 10.1093/jrsssc/qlae035
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Walking fingerprinting.
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- Journal of the Royal Statistical Society: Series C (Applied Statistics), 2024, v. 73, n. 5, p. 1221, doi. 10.1093/jrsssc/qlae033
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Spatio-temporal forecasting for the US Drought Monitor.
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- Journal of the Royal Statistical Society: Series C (Applied Statistics), 2024, v. 73, n. 5, p. 1203, doi. 10.1093/jrsssc/qlae032
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A fractional Hawkes process model for earthquake aftershock sequences.
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- Journal of the Royal Statistical Society: Series C (Applied Statistics), 2024, v. 73, n. 5, p. 1185, doi. 10.1093/jrsssc/qlae031
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Learning local cascading failure pattern from massive network failure data.
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- Journal of the Royal Statistical Society: Series C (Applied Statistics), 2024, v. 73, n. 5, p. 1155, doi. 10.1093/jrsssc/qlae030
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- Article
Variable importance based interaction modelling with an application on initial spread of COVID-19 in China.
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- Journal of the Royal Statistical Society: Series C (Applied Statistics), 2024, v. 73, n. 5, p. 1134, doi. 10.1093/jrsssc/qlae029
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Two-phase biomarker studies for disease progression with multiple registries.
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- Journal of the Royal Statistical Society: Series C (Applied Statistics), 2024, v. 73, n. 5, p. 1111, doi. 10.1093/jrsssc/qlae028
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- Article