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.

1 2 | ```
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, num.lb = 10)
``` |

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

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