The default method constructs a TSFmodel. Other methods extract a
TSFmodel from an object.
Usage
TSFmodel(obj, ...)
## Default S3 method:
TSFmodel(obj, f=NULL, Omega = NULL, Phi=NULL, LB = NULL,
positive.data=FALSE, names=NULL, ...)
## S3 method for class 'TSFmodel'
TSFmodel(obj, ...)
## S3 method for class 'FAmodel'
TSFmodel(obj, f=NULL, positive.data=FALSE, names=NULL, ...)
Arguments
obj
The loadings matrix (B) in the default (constructor) method.
In other methods, an object from which the model should be
extracted.
f
matrix of factor series.
Omega
Covariance of the idiosyncratic term.
Phi
Covariance of the factors.
LB
Factor score coefficient matrix.
positive.data
logical indicating if any resulting negative values
should be set to zero.
names
vector of strings indicating names to be given to output
series.
...
arguments passed to other methods or stored in the object.
Details
The default method is the constructor for TSFmodel objects. Other
methods extract a TSFmodel object from other objects that contain one.
The loadings and the factors must be supplied to the default method. Omega,
Phi, and LB are included when the object comes from an estimation method, but
are not necessary when the object is being specified in order to simulate.
The model is defined by
y(t) = B f(t) + eps(t),
where the factors f(t) have covariance Phi
and eps(t) have covariance Omega.
The loadings matrix B is M x k, where M
is the number of indicator variables
(the number of series in y) and k is the number of
factor series.
The estimation method estTSF.ML returns a TSFmodel as part of a
TSFestModel that has additional information about the estimation.
Value
A TSFmodel.
Author(s)
Paul Gilbert
See Also
simulate.TSFmodel,
simulate,
estTSF.ML
Examples
f <- matrix(c(2+sin(pi/100:1),5+3*sin(2*pi/5*(100:1))),100,2)
B <- t(matrix(c(0.9, 0.1,
0.8, 0.2,
0.7, 0.3,
0.5, 0.5,
0.3, 0.7,
0.1, 0.9), 2,6))
z <- TSFmodel(B, f=f)
tfplot(z)