hw: Height-Weight Covariance Study

Description Usage Format References Examples

Description

The data set highlights the importance of handling covariance when such information is available. If the covariance is not incorporated, hypothesis testing may lead to entirely difference conclusion.

Usage

1

Format

A data frame with 20 observations on the following 2 variables.

Height

the height of an individual

Weight

the weight of an individual

References

Rencher, A.C. (2002). Methods of Multivariate Analysis, 2e. J. Wiley.

Examples

1
2
3
4
5
6
7
8
data(hw)
sigma0 <- matrix(c(20, 100, 100, 1000),nrow=2)
sigma <- var(hw)
v <- nrow(hw)-1
p <- ncol(hw)
u <- v*(log(det(sigma0))-log(det(sigma)) + sum(diag(sigma%*%solve(sigma0)))-p)
u1 <- (1- (1/(6*v-1))*(2*p+1 - 2/(p+1)))*u
u;u1;qchisq(1-0.05,p*(p+1)/2)


ACSWR documentation built on May 19, 2017, 6:57 p.m.
Search within the ACSWR package
Search all R packages, documentation and source code

Questions? Problems? Suggestions? Tweet to @rdrrHQ or email at ian@mutexlabs.com.

Please suggest features or report bugs in the GitHub issue tracker.

All documentation is copyright its authors; we didn't write any of that.