fastmatrix (version 0.3-8)

cov.MSSD: Variance and covariance matrices

Description

Returns a list containing the mean and covariance matrix of the data.

Usage

cov.MSSD(x)

Arguments

x

a matrix or data frame. As usual, rows are observations and columns are variables.

Value

A list containing the following named components:

mean

an estimate for the center (mean) of the data.

cov

the estimated covariance matrix.

Details

This procedure uses the Holmes-Mergen method using the difference between each successive pairs of observations also known as Mean Square Successive Method (MSSD) to estimate the covariance matrix.

References

Holmes, D.S., Mergen, A.E. (1993). Improving the performance of the \(T^2\) control chart. Quality Engineering 5, 619-625.

See Also

cov and var.

Examples

# NOT RUN {
x <- cbind(1:10, c(1:3, 8:5, 8:10))
z0 <- cov(x)
z0
z1 <- cov.MSSD(x)
z1
# }