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[null,"1.","Record Nr.",null,"UNINA9910495161903321"]
[null,null,"Autore",null,"Hagiwara Junichiro"]
[null,null,"Titolo",null,"Time Series Analysis for the State-Space Model with R/Stan / / by Junichiro Hagiwara"]
[null,null,"Pubbl/distr/stampa",null,"Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2021"]
[null,null,"ISBN",null,"9789811607110"]
[{"$nulls":4},"9811607117"]
[null,null,"Edizione",null,"[1st ed. 2021.]"]
[null,null,"Descrizione fisica",null,"1 online resource (350 pages)"]
[null,null,"Disciplina",null,"519.55"]
[null,null,"Soggetti",null,"Statistics"]
[{"$nulls":4},"Mathematical statistics - Data processing"]
[{"$nulls":4},"Econometrics"]
[{"$nulls":4},"Macroeconomics"]
[{"$nulls":4},"Applied Statistics"]
[{"$nulls":4},"Statistics and Computing"]
[{"$nulls":4},"Bayesian Inference"]
[{"$nulls":4},"Statistical Theory and Methods"]
[{"$nulls":4},"Quantitative Economics"]
[{"$nulls":4},"Macroeconomics and Monetary Economics"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,"Nota di contenuto",null,"Introduction -- Fundamental of probability and statistics -- Fundamentals of handling time series data with R -- Quick tour of time series analysis -- State-space model -- State estimation in the state-space model -- Batch solution for linear Gaussian state-space model -- Sequential solution for linear Gaussian state-space model -- Introduction and analysis examples of a well-known component model -- Batch solution for general state-space model -- Sequential solution for general state-space model -- Example of applied analysis in general state-space model."]
[null,null,null,"Sommario/riassunto","This book provides a comprehensive and concrete illustration of time series analysis focusing on the state-space model, which has recently attracted increasing attention in a broad range of fields. The major feature of the book lies in its consistent Bayesian treatment regarding whole combinations of batch and sequential solutions for linear Gaussian and general state-space models: MCMC and Kalman/particle "]
[{"$nulls":4},"filter. The reader is given insight on flexible modeling in modern time series analysis. The main topics of the book deal with the state-space model, covering extensively, from introductory and exploratory methods to the latest advanced topics such as real-time structural change detection. Additionally, a practical exercise using R/Stan based on real data promotes understanding and enhances the reader’s analytical capability. ."]