Time Series Python

Deep Time Series Forecasting with Python  eBooks & eLearning

Posted by AlenMiler at Jan. 24, 2017
Deep Time Series Forecasting with Python

Deep Time Series Forecasting with Python: An Intuitive Introduction to Deep Learning for Applied Time Series Modeling by N D Lewis
English | 11 Dec. 2016 | ISBN: 1540809080 | 212 Pages | PDF (True) | 1.58 MB

Master Deep Time Series Forecasting with Python! Deep Time Series Forecasting with Python takes you on a gentle, fun and unhurried practical journey to creating deep neural network models for time series forecasting with Python.
Multivariate Modelling of Non-Stationary Economic Time Series (Palgrave Texts in Econometrics)

Multivariate Modelling of Non-Stationary Economic Time Series (Palgrave Texts in Econometrics) by John Hunter
English | 27 May 2017 | ISBN: 0230243304 | 518 Pages | EPUB | 3.9 MB

This book examines conventional time series in the context of stationary data prior to a discussion of cointegration, with a focus on multivariate models. The authors provide a detailed and extensive study of impulse responses and forecasting in the stationary and non-stationary context, considering small sample correction,

Time-Series Forecasting  eBooks & eLearning

Posted by DZ123 at Sept. 10, 2017
Time-Series Forecasting

Chris Chatfield, "Time-Series Forecasting"
English | 2000 | ISBN: 1584880635 | PDF | pages: 265 | 1.7 mb
Multivariate Modelling of Non-Stationary Economic Time Series (Palgrave Texts in Econometrics) [Repost]

Multivariate Modelling of Non-Stationary Economic Time Series (Palgrave Texts in Econometrics) by John Hunter
English | 27 May 2017 | ISBN: 0230243304 | 518 Pages | PDF | 5.3 MB

This book examines conventional time series in the context of stationary data prior to a discussion of cointegration, with a focus on multivariate models. The authors provide a detailed and extensive study of impulse responses and forecasting in the stationary and non-stationary context, considering small sample correction,
Richly Parameterized Linear Models: Additive, Time Series, and Spatial Models Using Random Effects (Repost)

James S. Hodges, "Richly Parameterized Linear Models: Additive, Time Series, and Spatial Models Using Random Effects"
English | ISBN: 143986683X | 2014 | 469 pages | PDF | 15 MB

Applied Econometric Time Series, 4 edition (Repost)  eBooks & eLearning

Posted by nebulae at Aug. 6, 2017
Applied Econometric Time Series, 4 edition (Repost)

Walter Enders, "Applied Econometric Time Series, 4 edition"
English | 2014 | ISBN: 1118808568 | 496 pages | PDF | 7 MB
Elements of Nonlinear Time Series Analysis and Forecasting (Springer Series in Statistics) [Repost]

Elements of Nonlinear Time Series Analysis and Forecasting (Springer Series in Statistics) by Jan G. De Gooijer
English | 20 Apr. 2017 | ISBN: 3319432516 | 642 Pages | PDF | 14.34 MB

This book provides an overview of the current state-of-the-art of nonlinear time series analysis, richly illustrated with examples, pseudocode algorithms and real-world applications.
R Data Analysis Solution – Analyzing Time-Series and Social Media Data, and More

R Data Analysis Solution – Analyzing Time-Series and Social Media Data, and More
MP4 | Video: AVC 1280x720 | Audio: AAC 44KHz 2ch | Duration: 2.5 Hours | 623 MB
Genre: eLearning | Language: English

Time Series Analysis and Its Applications: With R Examples, Fourth Edition  eBooks & eLearning

Posted by AvaxGenius at July 29, 2017
Time Series Analysis and Its Applications: With R Examples, Fourth Edition

Time Series Analysis and Its Applications: With R Examples, Fourth Edition By Robert H. Shumway, David S. Stoffer
English | EPUB | 2017 | 567 Pages | ISBN : 3319524518 | 9.66 MB

The fourth edition of this popular graduate textbook, like its predecessors, presents a balanced and comprehensive treatment of both time and frequency domain methods with accompanying theory. Numerous examples using nontrivial data illustrate solutions to problems such as discovering natural and anthropogenic climate change, evaluating pain perception experiments using functional magnetic resonance imaging, and monitoring a nuclear test ban treaty.
Elements of Nonlinear Time Series Analysis and Forecasting (Springer Series in Statistics) [Repost]

Elements of Nonlinear Time Series Analysis and Forecasting (Springer Series in Statistics) by Jan G. De Gooijer
English | 20 Apr. 2017 | ISBN: 3319432516 | 642 Pages | PDF | 14.34 MB

This book provides an overview of the current state-of-the-art of nonlinear time series analysis, richly illustrated with examples, pseudocode algorithms and real-world applications. Avoiding a “theorem-proof” format,