sampleCovMat {bayesSurv} | R Documentation

## Compute a sample covariance matrix.

### Description

This function computes a sample covariance matrix.

### Usage

    sampleCovMat(sample)

### Arguments

`sample` | a `matrix` or `data.frame` with sampled values in rows. I.e. number of rows of `sample` determines a sample size, number of columns of `sample` determines a dimension of the distribution from which it was sampled.

### Details

When y[1], ..., y[n] is a sequence of p-dimensional vectors y[i] the sample covariance matrix S is equal to

S = (1/(n-1)) sum[i=1][n] (y[i] - m)(y[i] - m)'

where

m = (1/n) sum[i=1][n] y[i].

When n=1 the function returns just sum of squares.

### Value

This function returns a matrix.

### Author(s)

Arnost Komarek arnost.komarek@med.kuleuven.be

### Examples

      ## Sample some values
      z1 <- rnorm(100, 0, 1)           ## first components of y
      z2 <- rnorm(100, 5, 2)           ## second components of y
      z3 <- rnorm(100, 10, 0.5)        ## third components of y

      ## Put them into a data.frame
      sample <- data.frame(z1, z2, z3)

      ## Compute a sample covariance matrix
      sampleCovMat(sample)

[Package bayesSurv version 0.4 Index]