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Algorithms and programs of dynamic mixture estimation : unified approach to different types of components / Ivan Nagy, Evgenia Suzdaleva
| Algorithms and programs of dynamic mixture estimation : unified approach to different types of components / Ivan Nagy, Evgenia Suzdaleva |
| Autore | Nagy, Ivan |
| Pubbl/distr/stampa | Cham, : Springer, 2017 |
| Descrizione fisica | XI, 113 p. : ill. ; 24 cm |
| Altri autori (Persone) | Suzdaleva, Evgenia |
| Soggetto topico |
62F10 - Point estimation [MSC 2020]
62H12 - Estimation in multivariate analysis [MSC 2020] 62-XX - Statistics [MSC 2020] 62F15 - Bayesian inference [MSC 2020] 62H30 - Classification and discrimination; cluster analysis (statistical aspects) [MSC 2020] |
| Soggetto non controllato |
Dynamic mixtures
Markov switching models Mixture estimation algorithms Mixture models Mixture prediction Mixtures of various distributions Open source programs Recursive Bayesian estimation |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Titolo uniforme | |
| Record Nr. | UNICAMPANIA-VAN0123391 |
Nagy, Ivan
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| Cham, : Springer, 2017 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
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Bayesian nonparametric data analysis / Peter Müller ... [et al.]
| Bayesian nonparametric data analysis / Peter Müller ... [et al.] |
| Pubbl/distr/stampa | [Cham], : Springer, 2015 |
| Descrizione fisica | XIV, 193 p. ; 24 cm |
| Soggetto topico |
62-XX - Statistics [MSC 2020]
62F15 - Bayesian inference [MSC 2020] 62G07 - Density estimation [MSC 2020] 62Gxx - Nonparametric inference [MSC 2020] 62C10 - Bayesian problems; characterization of Bayes procedures [MSC 2020] 60G57 - Random measures [MSC 2020] 62G05 - Nonparametric estimation [MSC 2020] 62N02 - Estimation in survival analysis and censored data [MSC 2020] |
| Soggetto non controllato |
Bayesian Statistics
Clustering Markov Chains Mixture models Monte Carlo Nonparametrics |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Titolo uniforme | |
| Record Nr. | UNICAMPANIA-VAN0113615 |
| [Cham], : Springer, 2015 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
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Case Studies in Applied Bayesian Data Science : CIRM Jean-Morlet Chair, Fall 2018 / Kerrie L. Mengersen, Pierre Pudlo, Christian P. Robert editors
| Case Studies in Applied Bayesian Data Science : CIRM Jean-Morlet Chair, Fall 2018 / Kerrie L. Mengersen, Pierre Pudlo, Christian P. Robert editors |
| Pubbl/distr/stampa | Cham, : Springer, 2020 |
| Descrizione fisica | vi, 417 p. : ill. ; 24 cm |
| Soggetto topico |
60Gxx - Stochastic processes [MSC 2020]
60J10 - Markov chains (discrete-time Markov processes on discrete state spaces) [MSC 2020] 62F15 - Bayesian inference [MSC 2020] 62P10 - Applications of statistics to biology and medical sciences; meta analysis [MSC 2020] 62M40 - Random fields; image analysis [MSC 2020] 62R07 - Statistical aspects of big data and data science [MSC 2020] 62H30 - Classification and discrimination; cluster analysis (statistical aspects) [MSC 2020] 62G05 - Nonparametric estimation [MSC 2020] |
| Soggetto non controllato |
Applied Data Science
Applied Statistics Bayesian Optimization Bayesian Statistics Bayesian computation Bayesian neural networks Big Data Case Studies in Data Science Case studies in Ecology Case studies in Health Composite likelihood Markov random fields Mixture models Spatial models |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Titolo uniforme | |
| Record Nr. | UNICAMPANIA-VAN0132626 |
| Cham, : Springer, 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
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Computational and Methodological Statistics and Biostatistics : Contemporary Essays in Advancement / Andriëtte Bekker, (Din) Ding-Geng Chen, Johannes T. Ferreira editors
| Computational and Methodological Statistics and Biostatistics : Contemporary Essays in Advancement / Andriëtte Bekker, (Din) Ding-Geng Chen, Johannes T. Ferreira editors |
| Pubbl/distr/stampa | Cham, : Springer, 2020 |
| Descrizione fisica | xxiv, 543 p. : ill. ; 24 cm |
| Soggetto topico |
62-XX - Statistics [MSC 2020]
00B15 - Collections of articles of miscellaneous specific interest [MSC 2020] 62P10 - Applications of statistics to biology and medical sciences; meta analysis [MSC 2020] |
| Soggetto non controllato |
Bayesian Statistics
Bayesian adaptive designs Censoring Circular distributions Extreme values Generalizability theory Mixture models Optimization Regression Modeling Regression modelling Robust regression Spatio-temporal Variable Selection |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Titolo uniforme | |
| Record Nr. | UNICAMPANIA-VAN0248829 |
| Cham, : Springer, 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
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Heterogeneity in Statistical Genetics : How to Assess, Address, and Account for Mixtures in Association Studies / Derek Gordon, Stephen J. Finch, Wonkuk Kim
| Heterogeneity in Statistical Genetics : How to Assess, Address, and Account for Mixtures in Association Studies / Derek Gordon, Stephen J. Finch, Wonkuk Kim |
| Autore | Gordon, Derek |
| Pubbl/distr/stampa | Cham, : Springer, 2020 |
| Descrizione fisica | xx, 352 p. : ill. ; 24 cm |
| Altri autori (Persone) |
Finch, Stephen J.
Kim, Won Kuk |
| Soggetto topico | 92D10 - Genetics and epigenetics [MSC 2020] |
| Soggetto non controllato |
Biostatistics
Genomic Classification Genomic Misclassification Heterogeneity Longitudinal Phenotype Mixed models Mixture models Next-Generation Sequencing Phenotype Classification Phenotype Data Phenotype Misclassification Statistical genetics |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Titolo uniforme | |
| Record Nr. | UNICAMPANIA-VAN0249338 |
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Gordon, Derek
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| Cham, : Springer, 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
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Mixture and Hidden Markov Models with R / Ingmar Visser, Maarten Speekenbrink
| Mixture and Hidden Markov Models with R / Ingmar Visser, Maarten Speekenbrink |
| Autore | Visser, Ingmar |
| Pubbl/distr/stampa | Cham, : Springer, 2022 |
| Descrizione fisica | xvi, 267 p. : ill. ; 24 cm |
| Altri autori (Persone) | Speekenbrink, Maarten |
| Soggetto non controllato |
Hidden Markov models
Latent class models Maximum likelihood estimation Mixture models Multivariate Multivariate time series R Programming Statistical Theory Time series Univariate Univariate time series |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNICAMPANIA-VAN0277950 |
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Visser, Ingmar
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| Cham, : Springer, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
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New Frontiers in Bayesian Statistics : BAYSM 2021, Online, September 1–3 / Raffaele Argiento, Federico Camerlenghi, Sally Paganin editors
| New Frontiers in Bayesian Statistics : BAYSM 2021, Online, September 1–3 / Raffaele Argiento, Federico Camerlenghi, Sally Paganin editors |
| Pubbl/distr/stampa | Cham, : Springer, 2022 |
| Descrizione fisica | xi, 117 p. : ill. ; 24 cm |
| Soggetto non controllato |
Bayesian Statistics
Bayesian nonparametrics Markov chain Mixture models Monte Carlo algorithms Structural Learning Survival analysis |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNICAMPANIA-VAN0277965 |
| Cham, : Springer, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
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Ten Projects in Applied Statistics / Peter McCullagh
| Ten Projects in Applied Statistics / Peter McCullagh |
| Autore | McCullagh, Peter |
| Pubbl/distr/stampa | Cham, : Springer, 2022 |
| Descrizione fisica | xix, 412 p. : ill. ; 24 cm |
| Soggetto non controllato |
Data analysis
Design of experiments Likelihood Function Linear Models Mixture models Spatio-temporal processes |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNICAMPANIA-VAN0278171 |
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McCullagh, Peter
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| Cham, : Springer, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
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