| 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))