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.
Methods in Brain Connectivity Inference through Multivariate Time Series Analysis (repost)

Koichi Sameshima, "Methods in Brain Connectivity Inference through Multivariate Time Series Analysis"
English | ISBN: 1439845727 | 2014 | 282 pages | PDF | 16 MB

Macroeconometrics and Time Series Analysis (The New Palgrave Economics Collection)  eBooks & eLearning

Posted by thingska at April 27, 2017
Macroeconometrics and Time Series Analysis (The New Palgrave Economics Collection)

Macroeconometrics and Time Series Analysis (The New Palgrave Economics Collection) by Steven Durlauf
English | 2009 | ISBN: 023023884X, 9780230238848, B01FY9ZAE2 | 406 Pages | PDF | 2.94 MB

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

Posted by AvaxGenius at April 25, 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 | PDF | 2017 | 567 Pages | ISBN : 3319524518 | 16.84 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.

Time Series Based Predictive Analytics Modelling: Using MS Excel  eBooks & eLearning

Posted by naag at April 24, 2017
Time Series Based Predictive Analytics Modelling: Using MS Excel

Time Series Based Predictive Analytics Modelling: Using MS Excel
2017 | English | ASIN: B01N9C1RI1 | 354 pages | PDF + EPUB (conv) | 29 Mb
Time Series Analysis: Nonstationary and Noninvertible Distribution Theory, 2nd edition

Katsuto Tanaka, "Time Series Analysis: Nonstationary and Noninvertible Distribution Theory, 2nd edition"
English | ISBN: 1119132096 | 2017 | 904 pages | PDF | 11 MB
Econometric Modelling with Time Series: Specification, Estimation and Testing (repost)

Econometric Modelling with Time Series: Specification, Estimation and Testing (Themes in Modern Econometrics) by Vance Martin, Stan Hurn and David Harris
English | 2012 | ISBN: 0521139813 , 0521196604 | 937 pages | PDF | 7,5 MB
Neural Networks for Time Series Forecasting with R: An Intuitive Step by Step Blueprint for Beginners

Neural Networks for Time Series Forecasting with R: An Intuitive Step by Step Blueprint for Beginners by N.D Lewis
English | 9 Apr. 2017 | ASIN: B06Y5F38P3 | 238 Pages | PDF | 2.01 MB

Multivariate Time Series Analysis: With R and Financial Applications (repost)  eBooks & eLearning

Posted by libr at April 9, 2017
Multivariate Time Series Analysis: With R and Financial Applications (repost)

Multivariate Time Series Analysis: With R and Financial Applications by Ruey S. Tsay
English | 2013 | ISBN: 1118617908 | ISBN-13: 9781118617908 | 520 pages | PDF | 5,5 MB

Time-Series Prediction and Applications: A Machine Intelligence Approach  eBooks & eLearning

Posted by AvaxGenius at March 26, 2017
Time-Series Prediction and Applications: A Machine Intelligence Approach

Time-Series Prediction and Applications: A Machine Intelligence Approach By Amit Konar, Diptendu Bhattacharya
English | PDF | 2017 | 255 Pages | ISBN : 3319545965 | 5.08 MB

This book presents machine learning and type-2 fuzzy sets for the prediction of time-series with a particular focus on business forecasting applications.