tWLSA-package: Two way weighted least square approach for missing value...

In NishithPaul/tWLSA: Two way Kernel Weighted Least Squate Approach for Missing Value Imputation of Metabolomics Data

Description

This package implements a Kernel weight based two way weighted least square approach for missing value imputation of metabolomics data

Package:	tWLSA
Type:	Package
Version:	1.0
Date:	2021-01-01
License:	GPL
Depends:	R (>=2.10)

Package tWLSA has the following functions:

chkMiss():	This function check the missing values in the dataset
	function.
chkOutliers():	This function Checks row wise outliers in a data matrix
	function.
chkOutMiss():	This function Checks both outliers and missing values data matrix
	function.
missChkOut():	This function checks the outliers
	function.
removeOut():	This function clean the outliers
	function.
wlsMisImp():	This function impute the missing values using two way kernel weight based least square approach

Nishith Kumar
Maintainer: Nishith Kumar <[e-mail]>

package

NishithPaul/tWLSA documentation built on Jan. 2, 2021, 12:33 a.m.