KFAS (version 1.0.3)

transformSSM: Transform the SSModel object with multivariate observations

Description

Function transform.SSModel transforms original model by LDL decomposition or state vector augmentation,

Usage

transformSSM(object, type = c("ldl", "augment"))

Arguments

object

State space model object from function SSModel.

type

Option 'ldl' performs LDL decomposition for covariance matrix $H_t$, and multiplies the observation equation with the $L_t^{-1}$, so $\epsilon_t^* \sim N(0,D_t)$. Option 'augment' adds $\epsilon_t$ to the state

Value

• model
  Transformed model.

Details

As all the functions in KFAS use univariate approach, $H_t$, a covariance matrix of an observation equation needs to be either diagonal or zero matrix. Function transformSSM performs either the LDL decomposition of the covariance matrix of the observation equation, or augments the state vector with the disturbances of the observation equation. In case of a LDL decomposition, the new $H_t$ contains the diagonal part of the decomposition, whereas observations $y_t$ and system matrices $Z_t$ are multiplied with the inverse of $L_t$.