ols_KCV

ols_KCV makes the K-Fold Cross Validation for ordinary least squared regression

Implements optimization techniques for Lasso regression, R.Tibshirani(1996)<doi:10.1111/j.2517-6161.1996.tb02080.x> using Fast Iterative Shrinkage-Thresholding Algorithm (FISTA) and Iterative Shrinkage-Thresholding Algorithm (ISTA) based on proximal operators, A.Beck(2009)<doi:10.1137/080716542>. The package is useful for high-dimensional regression problems and includes cross-validation procedures to select optimal penalty parameters.

YingHong Chen

ProxReg

Linear Models for Prediction and Classification using Proximal
Operators

Ferran Reverter Comes

Esteban Vegas Lozano

ols_KCV function

<dl><dt>data</dt>
<dd>full dataset which will be used for KCV</dd>
<dt>k</dt>
<dd>integer, which indicates how many training and test set will be splited from the dataset</dd>
<dt>y</dt>
<dd>dependent variable</dd>
<dt>x</dt>
<dd>independent variables</dd></dl>

Arguments

K-Fold Cross Validation for OLS — ols_KCV

<dl>

<dt>data</dt>
<dd>full dataset which will be used for KCV</dd>


<dt>k</dt>
<dd>integer, which indicates how many training and test set will be splited from the dataset</dd>


<dt>y</dt>
<dd>dependent variable</dd>


<dt>x</dt>
<dd>independent variables</dd>

</dl>

ols_KCV: K-Fold Cross Validation for OLS

Description

Usage

Value

Arguments

Examples