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Applied time series analysis and forecasting with Python

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Applied time series analysis and forecasting with Pythonby Changquan Huang, Alla Petukhina.
作者:	Huang, Changquan.
其他作者:	Petukhina, Alla.
出版者:	Cham :Springer International Publishing :2022.
面頁冊數:	x, 372 p. :ill. (chiefly color), digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	Time-series analysis.
電子資源:	https://doi.org/10.1007/978-3-031-13584-2
ISBN:	9783031135842$q(electronic bk.)

Applied time series analysis and forecasting with Python
Huang, Changquan.

Applied time series analysis and forecasting with Python[electronic resource] /by Changquan Huang, Alla Petukhina. - Cham :Springer International Publishing :2022. - x, 372 p. :ill. (chiefly color), digital ;24 cm. - Statistics and computing,2197-1706. - Statistics and computing..

This textbook presents methods and techniques for time series analysis and forecasting and shows how to use Python to implement them and solve data science problems. It covers not only common statistical approaches and time series models, including ARMA, SARIMA, VAR, GARCH and state space and Markov switching models for (non)stationary, multivariate and financial time series, but also modern machine learning procedures and challenges for time series forecasting. Providing an organic combination of the principles of time series analysis and Python programming, it enables the reader to study methods and techniques and practice writing and running Python code at the same time. Its data-driven approach to analyzing and modeling time series data helps new learners to visualize and interpret both the raw data and its computed results. Primarily intended for students of statistics, economics and data science with an undergraduate knowledge of probability and statistics, the book will equally appeal to industry professionals in the fields of artificial intelligence and data science, and anyone interested in using Python to solve time series problems.

ISBN: 9783031135842$q(electronic bk.)

Standard No.: 10.1007/978-3-031-13584-2doiSubjects--Topical Terms:

181890
Time-series analysis.

LC Class. No.: QA280 / .H83 2022

Dewey Class. No.: 519.55

Applied time series analysis and forecasting with Python
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