Description Usage Arguments Details Value Side Effects References See Also Examples

A periodic autoregression can be represented as an infinite periodic moving average process. This function calculates the coefficients in this expansion. These coefficients are needed in various time series computations such as in computing the variances of forecasts, variances of residual autocorrelations and theoretical autocovariances of a periodic autoregression. The function pepsi is used by pear to calculate the estimated standard deviations of the residual autocorrelations in a fitted periodic autoregression.

1 | ```
pepsi(phi, lag.max)
``` |

`phi` |
matrix with (i,j)-entry phi[i, j] where phi[i,j] is the autoregressive coefficient for period i at lag j. Here i=1,...,p and j=1,...,m where m is highest ar order specified. |

`lag.max` |
maximum number of lags to calculate in the moving average expansion. |

The moving average expansion for a periodic autoregressive is defined in equation (1.4) of McLeod (1994) and the algorithm implements the recursion given in equation (1.5).

matrix with (i,j)-entry psi[i, j] where psi[i,j] is the autoregressive coefficient for period i at lag j. Here i=1,...,p and j=1,...,lag.max.

none

McLeod, A.I. (1994), "Diagnostic Checking of Periodic Autoregression" Journal of Time Series Analysis, Vol. 15, No. 2, pp.221–233.

pear

1 2 3 |

Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.