opsr.fit {OPSR} | R Documentation |
This is the basic computing engine called by opsr
used to fit ordinal
probit switching regression models. Should usually not be used directly.
The log-likelihood function is implemented in C++ which yields a considerable
speed-up. Parallel computation is implemented using OpenMP
.
opsr.fit(
Ws,
Xs,
Ys,
start,
fixed,
weights,
method,
iterlim,
printLevel,
nThreads,
.useR = FALSE,
...
)
Ws |
list of matrices with explanatory variables for selection process for each regime. |
Xs |
list of matrices with expalanatory varialbes for outcome process for each regime. |
Ys |
list of vectors with continuous outcomes for each regime. |
start |
a numeric vector with the starting values (passed to |
fixed |
parameters to be treated as constants at their |
weights |
a vector of weights to be used in the fitting process. Has to
conform with order ( |
method |
maximzation method (passed to |
iterlim |
maximum number of iterations (passed to |
printLevel |
larger number prints more working information (passed to |
nThreads |
number of threads to be used. Do not pass higher number than
number of ordinal outcomes. See also |
.useR |
if |
... |
further arguments passed to |
object of class "maxLik" "maxim"
.
maxLik::maxLik
, loglik_cpp
, opsr