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Type: Package
Title: Multiple Correlation
Version: 0.1.1
Author: Abirami S
Maintainer: Abirami S <abirami89@gmail.com>
Description: Computes multiple correlation coefficient when the data matrix is given and tests its significance.
Depends: R (≥ 3.1.0), MASS,matrixcalc
License: GPL-2
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2017-04-16 15:29:21 UTC; Sampath
Repository: CRAN
Date/Publication: 2017-04-16 16:24:55 UTC

Multiple Correlation

Description

Computes Mutliple Correlation Coefficient between one variable and a set of variables

Usage

mcr(dda, ld, rd, rawdata = T)

Arguments

dda

Data

ld

Dependent Variable

rd

vector of independent variables

rawdata

a boolean variable taking F if the input is a correlation matrix T if it is data matrix

Value

Returns the value of Multiple Correlation between dependent and independent variables

Author(s)

Abirami S

Examples


## Example 1:
mcr(iris[,-5],1,c(2,3,4))  ## Returns multiple correlation between Sepal.Length
                          ## and the other variables

## Example 2
mu<-c(10,12,13,14)
sig<-matrix(0,4,4)
diag(sig)<-c(2,1,1,3)
da<-MASS::mvrnorm(25,mu,sig)
mcr(da, 2,c(1,3,4))       ## Returns Multiple correlation when the data matrix
                          ## simulated from a quadrivariate normal distribution
                          ## is given as input

## Example 3
da<-var(iris[,-5])
mcr(da,3,c(1,2,4),FALSE) ## Returns multiple correlation between Petal.Width
                         ## and the other variables when the correlation matrix
                         ## is given as input


Multiple Correlation Test of Significance

Description

Tests the significance of mutliple correlation coefficient

Usage

mcr.test(x, ld, rd)

Arguments

x

Data Matrix or Variance Covariance or Correlation matrix

ld

Label of dependent Variable

rd

Vector of labels of independent variables

Value

a htest class object

Author(s)

Abirami S

Examples

## Example
library(MASS)
mu<-c(10,12,13,14)
sig<-matrix(0,4,4)
diag(sig)<-c(2,1,1,2)
da<-mvrnorm(25,mu,sig)
mcr.test(da,1,c(2:4))

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