rstandard.KFS {KFAS}R Documentation

Extract Standardized Residuals from KFS output

Description

Extract Standardized Residuals from KFS output

Usage

## S3 method for class 'KFS'
rstandard(model, type = c("recursive", "pearson", "state"),
  standardization_type = c("marginal", "cholesky"), zerotol = 0, ...)

Arguments

model

KFS object

type

Type of residuals. See details.

standardization_type

Type of standardization. Either "marginal" (default) for marginal standardization or "cholesky" for Cholesky-type standardization.

zerotol

Tolerance parameter for positivity checking in standardization. Default is zero. The values of D <= zerotol * max(D, 0) are deemed to zero.

...

Ignored.

Details

For object of class KFS with fully Gaussian observations, several types of standardized residuals can be computed. Also the standardization for multivariate residuals can be done either by Cholesky decomposition L^(-1)[t]residual[t] or component-wise residual[t]/sd(residual[t]).

Examples

modelNile <- SSModel(Nile ~ SSMtrend(1, Q = list(matrix(NA))), H = matrix(NA))
modelNile <- fitSSM(inits = c(log(var(Nile)),log(var(Nile))), model = modelNile,
  method = "BFGS")$model
# Filtering and state smoothing
out <- KFS(modelNile, smoothing = c("state", "mean", "disturbance"))

plot(cbind(
    recursive = rstandard(out),
    irregular = rstandard(out, "pearson"),
    state = rstandard(out, "state")),
  main = "recursive and auxiliary residuals")

[Package KFAS version 1.3.7 Index]