copula based markov models time de sun li hsien (13 resultados)

Condición: New.

Condición: New.

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PF. Condición: New.

Condición: New. pp. 125.

Paperback. Condición: Brand New. 148 pages. 9.25x6.10x0.35 inches. In Stock.

Taschenbuch. Condición: Neu. Copula-Based Markov Models for Time Series | Parametric Inference and Process Control | Li-Hsien Sun (u. a.) | Taschenbuch | xvi | Englisch | 2020 | Springer Singapore | EAN 9789811549977 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book provides statistical methodologies for time series data, focusing on copula-based Markov chain models for serially correlated time series. It also includes data examples from economics, engineering, finance, sport and other disciplines to illustrate the methods presented. An accessible textbook for students in the fields of economics, management, mathematics, statistics, and related fields wanting to gain insights into the statistical analysis of time series data using copulas, the book also features stand-alone chapters to appeal to researchers.As the subtitle suggests, the book highlights parametric models based on normal distribution, t-distribution, normal mixture distribution, Poisson distribution, and others. Presenting likelihood-based methods as the main statistical tools for fitting the models, the book details the development of computing techniques to find the maximum likelihood estimator. It also addresses statistical process control, as well as Bayesian and regression methods. Lastly, to help readers analyze their data, it provides computer codes (R codes) for most of the statistical methods.

Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book provides statistical methodologies for time series data, focusing on copula-based Markov chain models for serially correlated time series. It also includes data examples from economics, engineering, finance, sport and other disciplines to illustrate the methods presented. An accessible textbook for students in the fields of economics, management, mathematics, statistics, and related fields wanting to gain insights into the statistical analysis of time series data using copulas, the book also features stand-alone chapters to appeal to researchers.As the subtitle suggests, the book highlights parametric models based on normal distribution, t-distribution, normal mixture distribution, Poisson distribution, and others. Presenting likelihood-based methods as the main statistical tools for fitting the models, the book details the development of computing techniques to find the maximum likelihood estimator. It also addresses statistical process control, as well as Bayesian and regression methods. Lastly, to help readers analyze their data, it provides computer codes (R codes) for most of the statistical methods. 148 pp. Englisch.

Condición: New. Print on Demand pp. 125.

Condición: New. PRINT ON DEMAND pp. 125.

Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Serves as introductory textbook on the analysis of time series data for students majoring in statistics and related fields &nbspIncludes numerous real-world data examples as well as R codes for implementation &nbspDiscusses .

Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book provides statistical methodologies for time series data, focusing on copula-based Markov chain models for serially correlated time series. It also includes data examples from economics, engineering, finance, sport and other disciplines to illustrate the methods presented. An accessible textbook for students in the fields of economics, management, mathematics, statistics, and related fields wanting to gain insights into the statistical analysis of time series data using copulas, the book also features stand-alone chapters to appeal to researchers.As the subtitle suggests, the book highlights parametric models based on normal distribution, t-distribution, normal mixture distribution, Poisson distribution, and others. Presenting likelihood-based methods as the main statistical tools for fitting the models, the book details the development of computing techniques to find the maximum likelihood estimator. It also addresses statistical process control, as well as Bayesian and regression methods. Lastly, to help readers analyze their data, it provides computer codes (R codes) for most of the statistical methods.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 148 pp. Englisch.