Calculate Residuals Statistics and Likelihood
Calculate the residuals statistics and likelihood of a residual.
residualStats(pred, data, sampleT=nrow(pred), warn=TRUE)
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. |
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.
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.
residualStats(matrix(rnorm(200), 100,2), NULL) # but typically used for a residual
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