Learn R Programming

simts (version 0.1.1)

arma_to_wv_app: ARMA process to WV Approximation

Description

This function computes the (haar) WV of an ARMA process

Usage

arma_to_wv_app(ar, ma, sigma2, tau, alpha = 0.9999)

Arguments

ar

A vec containing the coefficients of the AR process

ma

A vec containing the coefficients of the MA process

sigma2

A double containing the residual variance

tau

A vec containing the scales e.g. \(2^{\tau}\)

alpha

A double indicating the cutoff.

Value

A vec containing the wavelet variance of the ARMA process.

Process Haar Wavelet Variance Formula

The Autoregressive Order \(p\) and Moving Average Order \(q\) (ARMA(\(p\),\(q\))) process has a Haar Wavelet Variance given by: $$\frac{{{\tau _j}\left[ {1 - \rho \left( {\frac{{{\tau _j}}}{2}} \right)} \right] + 2\sum\limits_{i = 1}^{\frac{{{\tau _j}}}{2} - 1} {i\left[ {2\rho \left( {\frac{{{\tau _j}}}{2} - i} \right) - \rho \left( i \right) - \rho \left( {{\tau _j} - i} \right)} \right]} }}{{\tau _j^2}}\sigma _X^2$$ where \(\sigma _X^2\) is given by the variance of the ARMA process. Furthermore, this assumes that stationarity has been achieved as it directly

Details

This function provides an approximation to the arma_to_wv as computation times were previously a concern. However, this is no longer the case and, thus, this has been left in for the curious soul to discover...