A function to estimate a (possibly big) multivariate VECM time series using penalized least squares methods, such as ENET, SCAD or MC+.
fitVECM(data, p, penalty, method, logScale, ...)
the data from the time series: variables in columns and observations in rows
order of the VECM model
the penalty function to use. Possible values are "ENET"
,
"SCAD"
or "MCP"
"cv"
or "timeSlice"
should the function consider the log
of the inputs? By default
this is set to TRUE
options for the function (TODO: specify)
Pi the matrix Pi
for the VECM model
G the list (of length p-1
) of the estimated matrices of the process
fit the results of the penalized LS estimation
mse the mean square error of the cross validation
time elapsed time for the estimation