var.cov.sum: Estimated sum of autocovariances from time series

Description Usage

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


For each time series in the columns of the data matrix, X, selects an optimal ARMA model (according to an information criteria); then, fits such model and analyses the corresponding residuals. If all the ARMA models are suitable, returns a vector containing the corresponding sums the autocovariances. If some ARMA model is not suitable, it informs the user with a message.


var.cov.sum(X = 1:100, lag.max = 50, p.max = 3, q.max = 3, ic = "BIC", 
alpha = 0.05, = 10)

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