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


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)

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