R: Multiple Correlation

mulcor {timsac} | R Documentation

## Multiple Correlation

### Description

Estimate multiple correlation.

### Usage

      mulcor(y, lag = NULL, plot = TRUE, lag_axis = TRUE)

### Arguments

`y` | a multivariate time series.
`lag` | maximum lag. Default is 2*sqrt(n), where n is the length of the time series `y`.
`plot` | logical. If TRUE (default), correlations `cor` are plotted.
`lag_axis` | logical. If `TRUE` (default) with plot=`TRUE`, x-axis is drawn.

### Value

`cov` | covariances.
`cor` | correlations (normalized covariances).
`mean` | mean.

### References

H.Akaike and T.Nakagawa (1988) Statistical Analysis and Control of Dynamic Systems. Kluwer Academic publishers.

### Examples

    # Example 1
    y <- rnorm(1000)
    dim(y) <- c(500,2)
    mulcor(y, lag_axis = FALSE)

    # Example 2
    xorg <- rnorm(1003)
    x <- matrix(0, nrow = 1000, ncol = 2)
    x[, 1] <- xorg[1:1000]
    x[, 2] <- xorg[4:1003] + 0.5*rnorm(1000)
    mulcor(x, lag = 20)

[Package timsac version 1.3.6 Index]