SCMfit: Scalar Component Model Fitting

In MTS: All-Purpose Toolkit for Analyzing Multivariate Time Series (MTS) and Estimating Multivariate Volatility Models

Scalar Component Model Fitting

Description

Perform estimation of a VARMA model specified via the SCM approach

Usage

SCMfit(da, scms, Tdx, include.mean = T, fixed = NULL, 
    prelim = F, details = F, thres = 1, ref = 0, 
    SCMpar=NULL, seSCMpar=NULL)

Arguments

da	The T-by-k data matrix of a k-dimensional time series
scms	A k-by-2 matrix of the orders of SCMs
Tdx	A k-dimensional vector for locating "1" of each row in the transformation matrix.
include.mean	A logical switch to include the mean vector. Default is to include mean vector.
fixed	A logical matrix to set parameters to zero
prelim	A logical switch for preliminary estimation. Default is false.
details	A logical switch to control details of output
thres	Threshold for individual t-ratio when setting parameters to zero. Default is 1.
ref	A switch to use SCMmod in model specification.
SCMpar	Parameter estimates of the SCM model, to be used in model refinement
seSCMpar	Standard errors of the parameter estimates in SCMpar

Details

Perform conditional maximum likelihood estimation of a VARMA model specified by the scalar component model approach, including the transformation matrix.

Value

data	Observed time series
SCMs	The specified SCMs
Tdx	Indicator vector for the transformation matrix. The length of Tdx is k.
locTmtx	Specification of estimable parameters of the transformation matrix
locAR	Locators for the estimable parameters of the VAR coefficients
locMA	Locators for the estimable parameters of the VMA coefficients
cnst	A logical switch to include the constant vector in the model
coef	The parameter estimates
secoef	Standard errors of the parameter estimates
residuals	Residual series
Sigma	Residual covariance matrix
aic,bic	Information criteria of the fitted model
Ph0	Estimates of the constant vector, if any
Phi	Estimates of the VAR coefficients
Theta	Estimates of the VMA coefficients

Author(s)

Ruey S. Tsay

References

Tsay (2014, Chapter 4). Multivariate Time Series Analysis with R and Financial Applications. John Wiley. Hoboken, NJ.

MTS documentation built on April 11, 2022, 5:07 p.m.