Trading Use r

Meta-Analysis with R (Use R!) (Repost)  eBooks & eLearning

Posted by insetes at Nov. 21, 2017
Meta-Analysis with R (Use R!) (Repost)

Meta-Analysis with R (Use R!) By Guido Schwarzer, James R. Carpenter, Gerta Rücker
2015 | 264 Pages | ISBN: 3319214152 | PDF | 4 MB

Introductory Time Series with R (Use R!) (Repost)  eBooks & eLearning

Posted by insetes at Oct. 18, 2017
Introductory Time Series with R (Use R!) (Repost)

Introductory Time Series with R (Use R!) By Paul S. P. Cowpertwait, Andrew Metcalfe
2009 | 262 Pages | ISBN: 0387886974 | PDF | 6 MB

Nonlinear Regression with R (Use R!) (Repost)  eBooks & eLearning

Posted by insetes at Oct. 17, 2017
Nonlinear Regression with R (Use R!) (Repost)

Nonlinear Regression with R (Use R!) By Christian Ritz, Jens Carl Streibig
2008 | 150 Pages | ISBN: 0387096159 | PDF | 4 MB
Automated Trading with R: Quantitative Research and Platform Development [Repost]

Automated Trading with R: Quantitative Research and Platform Development by Christopher Conlan
English | 29 Sept. 2016 | ISBN: 148422177X | 236 Pages | EPUB | 1.33 MB

This book explains the broad topic of automated trading, starting with its mathematics and moving to its computation and execution. Readers will gain a unique insight into the mechanics and computational considerations taken in building a backtester, strategy optimizer, and fully functional trading platform.

Automated Trading with R: Quantitative Research and Platform Development  eBooks & eLearning

Posted by ksveta6 at Nov. 3, 2016
Automated Trading with R: Quantitative Research and Platform Development

Automated Trading with R: Quantitative Research and Platform Development by Christopher Conlan
2016 | ISBN: 148422177X | English | 205 pages | EPUB | 1 MB

Automated Trading with R: Quantitative Research and Platform Development  eBooks & eLearning

Posted by roxul at Oct. 31, 2016
Automated Trading with R: Quantitative Research and Platform Development

Christopher Conlan, "Automated Trading with R: Quantitative Research and Platform Development"
English | ISBN: 148422177X | 2016 | 236 pages | PDF | 7 MB
Automated Trading with R: Quantitative Research and Platform Development (1st Edition)

Automated Trading with R: Quantitative Research and Platform Development 1st ed. Edition
by Christopher Conlan

English | ISBN: 148422177X | 2016 | PDF | 205 pages | 6.70 MB

XML and Web Technologies for Data Sciences with R (Use R!) [Repost]  eBooks & eLearning

Posted by hill0 at Sept. 14, 2017
XML and Web Technologies for Data Sciences with R (Use R!) [Repost]

XML and Web Technologies for Data Sciences with R (Use R!) by Deborah Nolan
English | 27 Jan. 2014 | ISBN: 1461478995 | 663 Pages | PDF | 14.17 MB

Web technologies are increasingly relevant to scientists working with data, for both accessing data and creating rich dynamic and interactive displays. The XML and JSON data formats are widely used in Web services,

Analyzing Compositional Data with R (Use R!) (repost)  eBooks & eLearning

Posted by hill0 at April 17, 2017
Analyzing Compositional Data with R (Use R!) (repost)

Analyzing Compositional Data with R (Use R!) by K. Gerald van den Boogaart
English | 9 July 2013 | ISBN: 3642368085 | 276 Pages | PDF | 3.86 MB

This book covers statistical analysis of compositional data sets from basic principles to applications in descriptive exploratory analysis, robust linear models and advanced multivariate statistical methods. Offers many illustrated examples and code chunks.

Seamless R and C++ Integration with Rcpp (Use R!)  eBooks & eLearning

Posted by hill0 at April 17, 2017
Seamless R and C++ Integration with Rcpp (Use R!)

Seamless R and C++ Integration with Rcpp (Use R!) by Dirk Eddelbuettel
English | 4 Jun. 2013 | ISBN: 1461468671 | 248 Pages | EPUB | 410.14 KB

Rcpp is the glue that binds the power and versatility of R with the speed and efficiency of C++. With Rcpp, the transfer of data between R and C++ is nearly seamless, and high-performance statistical computing is finally accessible to most R users. Rcpp should be part of every statistician's toolbox. – Michael Braun, MIT Sloan School of Management