MARSS (version 3.2)

MARSSresids: MARSS standardized residuals

Description

Calculates the standardized residuals sensu Harvey, Koopman and Penzer (1998). This is a utility function in the MARSS-package.

Usage

MARSSresids(MLEobj)

Arguments

MLEobj

An object of class marssMLE. This object must have $par, $model and $kf elements containing MLE parameter estimates from e.g.

Value

• A list with the following components
• et
  The model residuals as a (n+m) x TT matrix with v_t on top and w_t below. This is hat(eta_t) on page 112 of Harvey, Koopman and Penzer (1998).
• var.et
  The variance of the model residuals as a (n+m) x (n+m) x TT matrix. This is var(hat(eta_t)).
• std.et
  The standardized model residuals as a (n+m) x TT matrix. This is et divided by the square root of var.et --- although the code is using the matrix equivalent of that equation.

Details

Uses the algorithm on page 112 of Harvey, Koopman and Penzer (1998) to compute the standardized model residuals.

References

Harvey, A., S. J. Koopman, and J. Penzer. 1998. Messy time series: a unified approach. Advances in Econometrics 13: 103-144 (see page 112). Koopman, S. J., N. Shephard, and J. A. Doornik. 1999. Statistical algorithms for models in state space using SsfPack 2.2. Econometrics Journal 2: 113-166. (see pages 147-148).

See Also

MARSSkem marssMLE

Examples

dat = t(harborSeal)
  dat = dat[c(2,11),]
  MLEobj = MARSS(dat)
  std.resids = MARSSresids(MLEobj)$std.et