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Communications in Statistics - Simulation and Computation Volume 37, 2007 - Issue 1
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Bayesian Inference

Bayesian Variable Selection in Markov Mixture Models

Roberta Paroli Dipartimento di Scienze Statistiche, Università Cattolica S.C., Milano, ItalyCorrespondence[email protected]
&
Luigi Spezia Dipartimento di Statistica, Università Ca' Foscari, Venezia, Italy
Pages 25-47 | Received 10 Jan 2007, Accepted 18 May 2007, Published online: 03 Jan 2008

Citations (13)

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Read on this site (3)

Dingjing Shi, Dexin Shi & Amanda J. Fairchild. (2023) Variable Selection for Mediators under a Bayesian Mediation Model. Structural Equation Modeling: A Multidisciplinary Journal 0:0, pages 1-14.
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Laura Deldossi & Roberta Paroli. (2015) Bayesian variable selection in a class of mixture models for ordinal data: a comparative study. Journal of Statistical Computation and Simulation 85:10, pages 1926-1944.
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Panagiotis Papastamoulis. (2014) Handling the Label Switching Problem in Latent Class Models Via the ECR Algorithm. Communications in Statistics - Simulation and Computation 43:4, pages 913-927.
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Articles from other publishers (10)

Luigi Spezia, Sheila Gibbs, Miriam Glendell, Rachel Helliwell, Roberta Paroli & Ina Pohle. (2023) Bayesian analysis of high-frequency water temperature time series through Markov switching autoregressive models. Environmental Modelling & Software 167, pages 105751.
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Adriano Zanin Zambom, Seonjin Kim & Nancy Lopes Garcia. (2021) Variable length Markov chain with exogenous covariates. Journal of Time Series Analysis 43:2, pages 312-328.
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Luigi Spezia. (2020) Bayesian variable selection in non-homogeneous hidden Markov models through an evolutionary Monte Carlo method. Computational Statistics & Data Analysis 143, pages 106840.
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Aliaksandr Hubin. (2019) An adaptive simulated annealing EM algorithm for inference on non-homogeneous hidden Markov models. An adaptive simulated annealing EM algorithm for inference on non-homogeneous hidden Markov models.
Takamitsu Araki, Kazushi Ikeda & Shotaro Akaho. (2015) An efficient sampling algorithm with adaptations for Bayesian variable selection. Neural Networks 61, pages 22-31.
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Luigi Spezia, Susan L. Cooksley, Mark J. Brewer, David Donnelly & Angus Tree. (2013) Mapping species distributions in one dimension by non-homogeneous hidden Markov models: the case of freshwater pearl mussels in the River Dee. Environmental and Ecological Statistics 21:3, pages 487-505.
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L. Spezia, S.L. Cooksley, M.J. Brewer, D. Donnelly & A. Tree. (2014) Modelling species abundance in a river by Negative Binomial hidden Markov models. Computational Statistics & Data Analysis 71, pages 599-614.
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Christian Birkel, Roberta Paroli, Luigi Spezia, Sarah M. Dunn, Doerthe Tetzlaff & Chris Soulsby. (2012) A new approach to simulating stream isotope dynamics using Markov switching autoregressive models. Advances in Water Resources 46, pages 20-30.
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Susan L. Cooksley, Mark J. Brewer, David Donnelly, Luigi Spezia & Angus Tree. (2012) Impacts of artificial structures on the freshwater pearl mussel Margaritifera margaritifera in the River Dee, Scotland . Aquatic Conservation: Marine and Freshwater Ecosystems 22:3, pages 318-330.
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Roberta Paroli & Luigi Spezia. (2008) Bayesian inference in non-homogeneous Markov mixtures of periodic autoregressions with state-dependent exogenous variables. Computational Statistics & Data Analysis 52:5, pages 2311-2330.
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