dlmodeler.check: Check dimensions and validity
In dlmodeler: Generalized Dynamic Linear Modeler

Description Usage Arguments Details Value Author(s) See Also Examples

Checks a dlmodeler object, in particular for the consistency of the dimensions of its elements.

1	dlmodeler.check(model, yt = NULL)

`model`	an object of class `dlmodeler` to check.
`yt`	an optional data vector to check with the model.

See dlmodeler for information about the state-space representation adopted in this package.

A list with the following information:

`status`	a boolean indicating whether the model is valid or not
`m`	dimension of state vector m
`r`	dimension of state disturbance covariance matrix r
`d`	dimension of observation vector d
`timevar`	a boolean indicating if the model has time-varying terms or not
`timevar.Tt`	the number of time steps in Tt, or NA if the matrix is constant
`timevar.Rt`	the number of time steps in Rt, or NA if the matrix is constant
`timevar.Qt`	the number of time steps in Qt, or NA if the matrix is constant
`timevar.Zt`	the number of time steps in Zt, or NA if the matrix is constant
`timevar.Ht`	the number of time steps in Ht, or NA if the matrix is constant

Cyrille Szymanski <cnszym@gmail.com>

dlmodeler, dlmodeler.build

require(dlmodeler)

# a stochastic level+trend DLM
mod <- dlmodeler.build(
		a0 = c(0,0), # initial state: (level, trend)
		P0 = diag(c(0,0)), # initial state variance set to...
		P0inf = diag(2), # ...use exact diffuse initialization
		matrix(c(1,0,1,1),2,2), # state transition matrix
		diag(c(1,1)), # state disturbance selection matrix
		diag(c(.5,.05)), # state disturbance variance matrix
		matrix(c(1,0),1,2), # observation design matrix
		matrix(1,1,1) # observation disturbance variance matrix
)
# print the model
mod
# check if it is valid
dlmodeler.check(mod)$status

# an empty DLM with 4 state variables (3 of which are stocastic)
# and bi-variate observations
mod <- dlmodeler.build(dimensions=c(4,3,2))
# print the model
mod
# check if it is valid
dlmodeler.check(mod)$status