Description

Extract Residuals of KFS output

Usage

Arguments

Details

For object of class KFS, several types of residuals can be computed:

• "recursive": One-step-ahead prediction residuals v[t,i]=y[t,i]-Z[t,i]a[t,i]. For non-Gaussian case recursive residuals are computed as y[t]-Z[t]a[t], i.e. non-sequentially. Computing recursive residuals for large non-Gaussian models can be time consuming as filtering is needed.

• "pearson":

  (y[t,i]-θ[t,i])V(μ[t,i])^(-0.5), i=1,…,p, t=1,…,n,

  where V(μ[t,i]) is the variance function of the series i

• "response": Data minus fitted values, y-E(y).

• "state": Residuals based on the smoothed disturbance terms η are defined as

  \hat η[t], t=1,…,n.

  Only defined for fully Gaussian models.