fitVECM: Multivariate VECM estimation

In svazzole/sparseVAR: Sparse VAR/VECM Models Estimation

Description

A function to estimate a (possibly big) multivariate VECM time series using penalized least squares methods, such as ENET, SCAD or MC+.

Usage

fitVECM(data, p, penalty, method, logScale, ...)

Arguments

data	the data from the time series: variables in columns and observations in rows
p	order of the VECM model
penalty	the penalty function to use. Possible values are "ENET", "SCAD" or "MCP"
method	"cv" or "timeSlice"
logScale	should the function consider the log of the inputs? By default this is set to TRUE
...	options for the function (TODO: specify)

Value

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

svazzole/sparseVAR documentation built on April 19, 2021, 2:11 p.m.