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  1. Bog
  2. Matematik
  3. Sandsynlighedsregning og statistik

Copula-Based Markov Models for Time Series

- Parametric Inference and Process Control
Af: Mohammed S. Alqawba, Takeshi Emura, Li-Hsien Sun, Xin-Wei Huang, Jong-Min Kim Engelsk Paperback

Copula-Based Markov Models for Time Series

- Parametric Inference and Process Control
Af: Mohammed S. Alqawba, Takeshi Emura, Li-Hsien Sun, Xin-Wei Huang, Jong-Min Kim Engelsk Paperback
Tjek vores konkurrenters priser

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.

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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.

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Se mere i:
Produktdetaljer
Sprog: Engelsk
Sider: 131
ISBN-13: 9789811549977
Indbinding: Paperback
Udgave:
ISBN-10: 9811549974
Kategori: Sandsynlighedsregning og statistik
Udg. Dato: 2 jul 2020
Længde: 0mm
Bredde: 155mm
Højde: 235mm
Forlag: Springer Verlag, Singapore
Oplagsdato: 2 jul 2020
Forfatter(e): Mohammed S. Alqawba, Takeshi Emura, Li-Hsien Sun, Xin-Wei Huang, Jong-Min Kim
Forfatter(e) Mohammed S. Alqawba, Takeshi Emura, Li-Hsien Sun, Xin-Wei Huang, Jong-Min Kim

Kategori Sandsynlighedsregning og statistik

ISBN-13 9789811549977

Sprog Engelsk

Indbinding Paperback

Sider 131

Udgave

Længde 0mm

Bredde 155mm

Højde 235mm

Udg. Dato 2 jul 2020

Oplagsdato 2 jul 2020

Forlag Springer Verlag, Singapore

Kategori sammenhænge