cov.wt {stats} | R Documentation |

## Weighted Covariance Matrices

### Description

Returns a list containing estimates of the weighted covariance matrix
and the mean of the data, and optionally of the (weighted) correlation
matrix.

### Usage

cov.wt(x, wt = rep(1/nrow(x), nrow(x)), cor = FALSE, center = TRUE)

### Arguments

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

`wt` |
a non-negative and non-zero vector of weights for each
observation. Its length must equal the number of rows of `x` . |

`cor` |
A logical indicating whether the estimated correlation
weighted matrix will be returned as well. |

`center` |
Either a logical or a numeric vector specifying the
centers to be used when computing covariances. If `TRUE` , the
(weighted) mean of each variable is used, if `FALSE` , zero is
used. If `center` is numeric, its length must equal the number
of columns of `x` . |

### Details

The covariance matrix is divided by one minus the sum of squares of
the weights, so if the weights are the default (*1/n*) the conventional
unbiased estimate of the covariance matrix with divisor *(n - 1)*
is obtained. This differs from the behaviour in S-PLUS.

### Value

A list containing the following named components:

`cov` |
the estimated (weighted) covariance matrix |

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

`n.obs` |
the number of observations (rows) in `x` . |

`wt` |
the weights used in the estimation. Only returned if given
as an argument. |

`cor` |
the estimated correlation matrix. Only returned if
`cor` is `TRUE` . |

### See Also

`cov`

and `var`

.

[Package

*stats* version 2.1.0

Index]