residualStats: Calculate Residuals Statistics and Likelihood

Description Usage Arguments Details Value See Also Examples

Description

Calculate the residuals statistics and likelihood of a residual.

Usage

1
    residualStats(pred, data, sampleT=nrow(pred), warn=TRUE)

Arguments

pred

A matrix with columns representing time series.

data

A matrix with columns representing time series.

sampleT

An integer indicating the sample to use.

warn

If FALSE certain warnings are suppressed.

Details

Residuals are calculated as pred[1:sampleT,,drop=FALSE] - data[1:sampleT,,drop=FALSE] and then statistics are calculated based on these residuals. If pred or data are NULL they are treated as zero.

Value

A list with elements like, cov, pred, and sampleT. pred and sampleT are as supplied (and are returned as this is a utility function called by other functions and it is convenient to pass them along). cov is the covariance of the residual and like is a vector of four elements representing the total, constant, determinant and covariance terms of the negative log likelihood function.

See Also

l

Examples

1
    residualStats(matrix(rnorm(200), 100,2), NULL) # but typically used for a residual

dse documentation built on May 2, 2019, 4:59 p.m.