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

In PLRModels: Statistical Inference in Partial Linear Regression Models

Estimated sum of autocovariances from time series

Description

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.

Usage

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

PLRModels documentation built on Aug. 19, 2023, 5:10 p.m.