similar to: New package lspls

Version 1.2-0 of the pls package is now available on CRAN. The pls package implements partial least squares regression (PLSR) and principal component regression (PCR). Features of the package include - Several plsr algorithms: orthogonal scores, kernel pls and simpls - Flexible cross-validation - A formula interface, with traditional methods like predict, coef, plot and summary - Functions

Version 1.2-0 of the pls package is now available on CRAN. The pls package implements partial least squares regression (PLSR) and principal component regression (PCR). Features of the package include - Several plsr algorithms: orthogonal scores, kernel pls and simpls - Flexible cross-validation - A formula interface, with traditional methods like predict, coef, plot and summary - Functions

Version 2.1-0 of the pls package is now available on CRAN. The pls package implements partial least squares regression (PLSR) and principal component regression (PCR). Features of the package include - Several plsr algorithms: orthogonal scores, kernel pls, wide kernel pls, and simpls - Flexible cross-validation - A formula interface, with traditional methods like predict, coef, plot and

Version 2.1-0 of the pls package is now available on CRAN. The pls package implements partial least squares regression (PLSR) and principal component regression (PCR). Features of the package include - Several plsr algorithms: orthogonal scores, kernel pls, wide kernel pls, and simpls - Flexible cross-validation - A formula interface, with traditional methods like predict, coef, plot and

Dear R user, I am looking for a code on double cross validation in LASSO , one for optimizing the parameter and other one is for MSEP. If any one have it, please foroward to me. I am using different package like LARS, chemometric etc. Thanks in advance Alex [[alternative HTML version deleted]]

Version 1.0-3 of the pls package is now available on CRAN. The pls package implements partial least squares regression (PLSR) and principal component regression (PCR). Features of the package include - Several plsr algorithms: orthogonal scores, kernel pls and simpls - Flexible cross-validation - A formula interface, with traditional methods like predict, coef, plot and summary - Functions

Version 1.1-0 of the pls package is now available on CRAN. The pls package implements partial least squares regression (PLSR) and principal component regression (PCR). Features of the package include - Several plsr algorithms: orthogonal scores, kernel pls and simpls - Flexible cross-validation - A formula interface, with traditional methods like predict, coef, plot and summary - Functions

Version 1.1-0 of the pls package is now available on CRAN. The pls package implements partial least squares regression (PLSR) and principal component regression (PCR). Features of the package include - Several plsr algorithms: orthogonal scores, kernel pls and simpls - Flexible cross-validation - A formula interface, with traditional methods like predict, coef, plot and summary - Functions

Version 1.2-1 of the pls package is now available on CRAN. This is mainly a bugfix-release. If you fit multi-response models, you are strongly engouraged to upgrade! The main changes since 1.2-0 are - Fixed bug in kernelpls.fit() that resulted in incorrect results when fitting mulitresponse models with fewer responses than predictors - Changed default radii in corrplot() - It is now

Version 1.2-1 of the pls package is now available on CRAN. This is mainly a bugfix-release. If you fit multi-response models, you are strongly engouraged to upgrade! The main changes since 1.2-0 are - Fixed bug in kernelpls.fit() that resulted in incorrect results when fitting mulitresponse models with fewer responses than predictors - Changed default radii in corrplot() - It is now

Version 2.0-0 of the pls package is now available on CRAN. The pls package implements partial least squares regression (PLSR) and principal component regression (PCR). Features of the package include - Several plsr algorithms: orthogonal scores, kernel pls and simpls - Flexible cross-validation - A formula interface, with traditional methods like predict, coef, plot and summary - Functions

Version 2.0-0 of the pls package is now available on CRAN. The pls package implements partial least squares regression (PLSR) and principal component regression (PCR). Features of the package include - Several plsr algorithms: orthogonal scores, kernel pls and simpls - Flexible cross-validation - A formula interface, with traditional methods like predict, coef, plot and summary - Functions

Version 1.0-3 of the pls package is now available on CRAN. The pls package implements partial least squares regression (PLSR) and principal component regression (PCR). Features of the package include - Several plsr algorithms: orthogonal scores, kernel pls and simpls - Flexible cross-validation - A formula interface, with traditional methods like predict, coef, plot and summary - Functions

Hi, I want to calculate PLS package in R. Now I want to calculate R, MSEP, RMSEP and R2 of PLSR and PCR using this. I also add this in library of R. How I can calculate R, MSEP, RMSEP and R2 of PLSR and PCR in R. I s any other method then please also suggest me. Simply I want to calculate these value. Thanking you. -- Nitish Kumar Mishra Junior Research Fellow BIC, IMTECH, Chandigarh, India

Dear friends, I'm confused about how to install packages from source. I just updated R in Lenny from http://cran.fiocruz.br/bin/linux/debian/ I included in sources.list: deb http://cran.fiocruz.br/bin/linux/debian lenny-cran/ deb-src http://cran.fiocruz.br/bin/linux/debian lenny-cran/ Then: apt-get update apt-get install r-base r-base-dev Then I downloaded the package

Hello i need some precision about nipals in the chemometrics package in R . When i use nipals in chemometrics i obtain T and P matrix. I really don't understand what to do with these two matrix to obtain the scores for every the component (like in spss fo example) Comp1 Comp2 Comp3 quest1 0,8434 0,54333 0,3466 quest2 0,665 0,7655 0,433 Thank you very

Greetings R Developers, I've been testing the alpha release of R-3.0.0 and I noticed that the plotting functionality in package tkrplot was not working correctly. Further diagnosis found the issue to be related to the command '.Tcl("image create Rplot plotname")' from package "tkrplot". The following example is taken from here:

For those R user's who don't subscribe to R-sig-db and are having troubles with the latest RMySQL binary on CRAN, please read the email thread at the end of this message. RMySQL 0.7-2 does work with MySQL 5.1, however the CRAN binary is linked against the 5.0 version. Best, Jeff -------- Original Message -------- Subject: Re: [R-sig-DB] Problems with RMySQL and MySQL server version

Dear All, A new task view "ChemPhys" on chemometrics and computational physics is available on CRAN (http://cran.r-project.org/web/views/ChemPhys.html). It describes packages and functions that are of use in modeling chemical/physical systems. Suggestions and comments regarding this task view are welcome. If you think a new category, package or function should be added, please mail.

David Ahern <dsahern at gmail.com> writes: > On 4/18/19 8:24 AM, Toke H?iland-J?rgensen wrote: >>>> >>> >>> Understood. Hopefully in March I will get some time to come back to this >>> and propose an idea on what I would like to see - namely, the admin has >>> a config option at load time to enable driver counters versus custom map