Works matching IS 00359254 AND DT 2025 AND VI 74 AND IP 1
Results: 12
Predicting 5G throughput with BAMMO, a boosted additive model for data with missing observations.
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- Journal of the Royal Statistical Society: Series C (Applied Statistics), 2025, v. 74, n. 1, p. 249, doi. 10.1093/jrsssc/qlae054
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Modelling particle number size distribution: a continuous approach.
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- Journal of the Royal Statistical Society: Series C (Applied Statistics), 2025, v. 74, n. 1, p. 229, doi. 10.1093/jrsssc/qlae053
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Sparse inference of the human haematopoietic system from heterogeneous and partially observed genomic data.
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- Journal of the Royal Statistical Society: Series C (Applied Statistics), 2025, v. 74, n. 1, p. 204, doi. 10.1093/jrsssc/qlae052
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tdCoxSNN: Time-dependent Cox survival neural network for continuous-time dynamic prediction.
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- Journal of the Royal Statistical Society: Series C (Applied Statistics), 2025, v. 74, n. 1, p. 187, doi. 10.1093/jrsssc/qlae051
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Extending the Dixon and Coles model: an application to women's football data.
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- Journal of the Royal Statistical Society: Series C (Applied Statistics), 2025, v. 74, n. 1, p. 167, doi. 10.1093/jrsssc/qlae050
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Nonhomogeneous hidden semi-Markov models for toroidal data.
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- Journal of the Royal Statistical Society: Series C (Applied Statistics), 2025, v. 74, n. 1, p. 142, doi. 10.1093/jrsssc/qlae049
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Determining the prior mean in Bayesian logistic regression with sparse data: a nonarbitrary approach.
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- Journal of the Royal Statistical Society: Series C (Applied Statistics), 2025, v. 74, n. 1, p. 126, doi. 10.1093/jrsssc/qlae048
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A Bayesian complex-valued latent variable model applied to functional magnetic resonance imaging.
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- Journal of the Royal Statistical Society: Series C (Applied Statistics), 2025, v. 74, n. 1, p. 100, doi. 10.1093/jrsssc/qlae046
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Measuring the impact of new risk factors within survival models.
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- Journal of the Royal Statistical Society: Series C (Applied Statistics), 2025, v. 74, n. 1, p. 83, doi. 10.1093/jrsssc/qlae045
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A noisy-input generalized additive model for relative sea-level change along the Atlantic coast of North America.
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- Journal of the Royal Statistical Society: Series C (Applied Statistics), 2025, v. 74, n. 1, p. 34, doi. 10.1093/jrsssc/qlae044
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Automatic locally stationary time series forecasting with application to predicting UK gross value added time series.
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- Journal of the Royal Statistical Society: Series C (Applied Statistics), 2025, v. 74, n. 1, p. 18, doi. 10.1093/jrsssc/qlae043
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Mixtures of Dirichlet processes for joint spatial modelling of transcranial magnetic stimulation mapping data.
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- Journal of the Royal Statistical Society: Series C (Applied Statistics), 2025, v. 74, n. 1, p. 1, doi. 10.1093/jrsssc/qlae042
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