var.cov.matrix: Estimated variance-covariance matrix from time series

Description Usage

View source: R/var.cov.matrix.R


Selects an optimal ARMA model (according to an information criteria) for the time series in the data vector, x; then, fits such model and analyses the corresponding residuals. If the ARMA model is suitable, returns the n x n variance-covariance matrix corresponding to n consecutive variables in the ARMA process. If the ARMA model is not suitable, it informs the user with a message.


var.cov.matrix(x = 1:100, n = 4, p.max = 3, q.max = 3, ic = "BIC",  p.arima=NULL, 
q.arima=NULL, alpha = 0.05, = 10)

PLRModels documentation built on May 29, 2017, 9:14 p.m.