R: Variance and covariance matrices

cov.MSSD {fastmatrix} | R Documentation

## 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.

### 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.

### Value

A list containing the following named components:

`mean` | an estimate for the center (mean) of the data.
`cov` | the estimated 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

    xy <- cbind(x = 1:10, y = c(1:3, 8:5, 8:10))
    z0 <- cov(xy)
    z0
    z1 <- cov.MSSD(xy)
    z1

[Package fastmatrix version 0.2-3571 Index]