sparsevar (version 0.0.3)

estimateVECM: Multivariate VECM 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

estimateVECM(data, p=2, penalty="ENET", logScale=TRUE, options=NULL)

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"

logScale

should the function consider the log of the inputs? By default this is set to TRUE

options

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