Topics in Empirical Finance With R And Rmetrics

Time Series: Applications to Finance with R and S-Plus (repost)  eBooks & eLearning

Posted by interes at April 3, 2014
Time Series: Applications to Finance with R and S-Plus (repost)

Time Series: Applications to Finance with R and S-Plus by Ngai Hang Chan
English | ISBN: 0470583622 | 2010 | PDF | 296 pages | 11 MB

A new edition of the comprehensive, hands-on guide to financial time series, now featuring S-Plus® and R software
Time Series: Applications to Finance with R and S-Plus®, Second Edition is designed to present an in-depth introduction to the conceptual underpinnings and modern ideas of time series analysis.

Time Series: Applications to Finance with R and S-Plus, 2nd Edition (Repost)  eBooks & eLearning

Posted by nebulae at April 29, 2012
Time Series: Applications to Finance with R and S-Plus, 2nd Edition (Repost)

Ngai Hang Chan "Time Series: Applications to Finance with R and S-Plus, 2nd Edition"
ISBN: 0470583622 | 2010 | PDF | 296 pages | 11 MB
Marketing Data Science: Modeling Techniques in Predictive Analytics with R and Python

Marketing Data Science: Modeling Techniques in Predictive Analytics with R and Python (FT Press Analytics) by Thomas W. Miller
English | May 22, 2015 | ISBN: 0133886557 | 480 Pages | AZW3/EPUB | 30.61 MB/26.61 MB

Now , a leader of Northwestern University's prestigious analytics program presents a fully-integrated treatment of both the business and academic elements of marketing applications in predictive analytics.

Applied Bayesian Statistics: With R and OpenBUGS Examples [Repost]  eBooks & eLearning

Posted by ChrisRedfield at Feb. 13, 2017
Applied Bayesian Statistics: With R and OpenBUGS Examples [Repost]

Mary Kathryn Cowles - Applied Bayesian Statistics: With R and OpenBUGS Examples
Published: 2013-01-03 | ISBN: 1461456959, 1489997040 | PDF | 232 pages | 2.9 MB

A First Course in Statistical Programming with R, Second Edition  eBooks & eLearning

Posted by Underaglassmoon at Jan. 9, 2017
A First Course in Statistical Programming with R, Second Edition

A First Course in Statistical Programming with R, Second Edition
Cambridge | English | July 2016 | ISBN-10: 1107576466 | 230 pages | PDF | 4.61 mb

By W. John Braun, University of British Columbia, Okanagan , Duncan J. Murdoch, University of Western Ontario

Global Leaders in Islamic Finance: Industry Milestones and Reflections (repost)  eBooks & eLearning

Posted by interes at Dec. 17, 2016
Global Leaders in Islamic Finance: Industry Milestones and Reflections (repost)

Global Leaders in Islamic Finance: Industry Milestones and Reflections by Emmy Abdul Alim
English | 2013 | ISBN: 1118465245 | 320 pages | PDF | 3 MB
Multivariate Nonparametric Regression and Visualization: With R and Applications to Finance (repost)

Multivariate Nonparametric Regression and Visualization: With R and Applications to Finance by Jussi Klemelä
English | 2014 | ISBN: 0470384425 | ISBN-13: 9780470384428 | 396 pages | PDF | 19,8 MB
Analyzing Event Statistics in Corporate Finance: Methodologies, Evidences, and Critiques (Repost)

Analyzing Event Statistics in Corporate Finance: Methodologies, Evidences, and Critiques By Jau-Lian Jeng
2015 | 200 Pages | ISBN: 1137397179 | PDF | 1 MB
Investing in Mortgage-Backed and Asset-Backed Securities, + Website: Financial Modeling with R and Open Source Analytics

Investing in Mortgage-Backed and Asset-Backed Securities, + Website: Financial Modeling with R and Open Source Analytics (Wiley Finance) by Glenn M. Schultz
2016 | ISBN: 1118944003 | English | 416 pages | PDF | 11 MB

Examples in Parametric Inference with R  eBooks & eLearning

Posted by Underaglassmoon at May 24, 2016
Examples in Parametric Inference with R

Examples in Parametric Inference with R
Springer | Statistical Theory and Methods | June 21, 2016 | ISBN-10: 9811008884 | 529 pages | pdf | 3.97 mb

Authors: Dixit, Ulhas Jayram
Exclusively focuses on statistical inference
Presents sophisticated mathematical proofs in a simple and easy-to-follow language
Discusses fundamental topics common to many fields of statistical inference, and which offer a point of departure for in-depth study