SEMIPARMA

Included are the procedure semiparma.g along with a file semiparma.rdme which
discusses installation and the estimation procedure.  Procedure semiparma.g is the main
procedure to call to estimate parameters of linear regression model with ARMA
errors. The main reference is Douglas Hodgson (1998), “Semiparametric Efficient
Estimation in Time Series Regression”, University of Rochester Manuscript.
Procedure computes semiparametric estimates of parameters of linear regression
model with ARMA errors in which the innovations to the ARMA process is
stationary and ergodic martingale difference sequence that is also 1st order Markov
process. Conditional density g(e(t)|e(t-1)) is assumed to be symmetric. The
semiparametric efficiency bound is also reported.
 
 

Download in Text format:   download wald.g
                                      download readme file
 
 

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