Time series : modeling, computation, and inference /
"Focusing on Bayesian approaches and computations using up-to-date simulation-based methods for inference, Time Series: Modeling, Computation, and Inference integrates mainstream approaches for time series modeling with significant recent developments in methodology and applications of time ser...
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| Language: | eng |
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Boca Raton : CRC Press,
c201
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| _version_ | 1796739239741751296 |
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| author | 518357 Prado, Raquel West, Mike, 1959- |
| author_facet | 518357 Prado, Raquel West, Mike, 1959- |
| author_sort | 518357 Prado, Raquel |
| collection | OCEAN |
| description | "Focusing on Bayesian approaches and computations using up-to-date simulation-based methods for inference, Time Series: Modeling, Computation, and Inference integrates mainstream approaches for time series modeling with significant recent developments in methodology and applications of time series analysis. It encompasses a graduate-level account of Bayesian time series modeling and analysis, a broad range of references to state-of-the-art approaches to univariate and multivariate time series analysis, and emerging topics at research frontiers. The book presents overviews of several classes of models and related methodology for inference, statistical computation for model fitting and assessment, and forecasting. The authors also explore the connections between time- and frequency-domain approaches and develop various models and analyses using Bayesian tools, such as Markov chain Monte Carlo (MCMC) and sequential Monte Carlo (SMC) methods. They illustrate the models and methods with examples and case studies from a variety of fields, including signal processing, biomedicine, and finance. Data sets, R and MATLABʼ code, and other material are available on the authors' websites. Along with core models and methods, this text offers sophisticated tools for analyzing challenging time series problems. It also demonstrates the growth of time series analysis into new application areas."--Publisher's description. |
| first_indexed | 2024-03-05T11:13:36Z |
| format | |
| id | KOHA-OAI-TEST:454599 |
| institution | Universiti Teknologi Malaysia - OCEAN |
| language | eng |
| last_indexed | 2024-03-05T11:13:36Z |
| publishDate | c201 |
| publisher | Boca Raton : CRC Press, |
| record_format | dspace |
| spelling | KOHA-OAI-TEST:4545992020-12-19T17:16:34ZTime series : modeling, computation, and inference / 518357 Prado, Raquel West, Mike, 1959- Boca Raton : CRC Press,c2010eng"Focusing on Bayesian approaches and computations using up-to-date simulation-based methods for inference, Time Series: Modeling, Computation, and Inference integrates mainstream approaches for time series modeling with significant recent developments in methodology and applications of time series analysis. It encompasses a graduate-level account of Bayesian time series modeling and analysis, a broad range of references to state-of-the-art approaches to univariate and multivariate time series analysis, and emerging topics at research frontiers. The book presents overviews of several classes of models and related methodology for inference, statistical computation for model fitting and assessment, and forecasting. The authors also explore the connections between time- and frequency-domain approaches and develop various models and analyses using Bayesian tools, such as Markov chain Monte Carlo (MCMC) and sequential Monte Carlo (SMC) methods. They illustrate the models and methods with examples and case studies from a variety of fields, including signal processing, biomedicine, and finance. Data sets, R and MATLABʼ code, and other material are available on the authors' websites. Along with core models and methods, this text offers sophisticated tools for analyzing challenging time series problems. It also demonstrates the growth of time series analysis into new application areas."--Publisher's description.Includes bibliographical references (p. 321-337) and indexesNotation, definitions, and basic inference -- Traditional time domain models -- The frequency domain -- Dynamic linear models -- State-space TVAR models -- SMC methods for state-space models -- Mixture models in time series -- Topics and examples in multiple time series -- Vector AR and ARMA models -- Multivariate DLMs and covariance models."Focusing on Bayesian approaches and computations using up-to-date simulation-based methods for inference, Time Series: Modeling, Computation, and Inference integrates mainstream approaches for time series modeling with significant recent developments in methodology and applications of time series analysis. It encompasses a graduate-level account of Bayesian time series modeling and analysis, a broad range of references to state-of-the-art approaches to univariate and multivariate time series analysis, and emerging topics at research frontiers. The book presents overviews of several classes of models and related methodology for inference, statistical computation for model fitting and assessment, and forecasting. The authors also explore the connections between time- and frequency-domain approaches and develop various models and analyses using Bayesian tools, such as Markov chain Monte Carlo (MCMC) and sequential Monte Carlo (SMC) methods. They illustrate the models and methods with examples and case studies from a variety of fields, including signal processing, biomedicine, and finance. Data sets, R and MATLABʼ code, and other material are available on the authors' websites. Along with core models and methods, this text offers sophisticated tools for analyzing challenging time series problems. It also demonstrates the growth of time series analysis into new application areas."--Publisher's description.PSZJBLNBKTime-series analysisURN:ISBN:9781420093360 |
| spellingShingle | Time-series analysis 518357 Prado, Raquel West, Mike, 1959- Time series : modeling, computation, and inference / |
| title | Time series : modeling, computation, and inference / |
| title_full | Time series : modeling, computation, and inference / |
| title_fullStr | Time series : modeling, computation, and inference / |
| title_full_unstemmed | Time series : modeling, computation, and inference / |
| title_short | Time series : modeling, computation, and inference / |
| title_sort | time series modeling computation and inference |
| topic | Time-series analysis |
| work_keys_str_mv | AT 518357pradoraquel timeseriesmodelingcomputationandinference AT westmike1959 timeseriesmodelingcomputationandinference |