rtvAR1: Simulation of Time Series with Time-varying Autocovariance

View source: R/rtvAR1.R

rtvAR1R Documentation

Simulation of Time Series with Time-varying Autocovariance

Description

Simulating time-varying variance based on TV-AR1 model

Usage

rtvAR1(n, sigma = 0.93)

Arguments

n

Length of the time series

sigma

Parameter σ^2 in TV-AR1, i.e. the variance. Default is 0.93.

Details

Time varying autoregressive processes of order 1 (TV-AR1) is

x_t = a_t x_(t-1) + ε_t,

with x_0=0, ε_t is iid N(0, σ^2) and a_t = 0.5\cos(2π t/T).

Value

The simulated series as a ts object.

Author(s)

Sara Taskinen, Markus Matilainen

References

Patilea V. and Raïssi H. (2014) Testing Second-Order Dynamics for Autoregressive Processes in Presence of Time-Varying Variance, Journal of the American Statistical Association, 109 (507), 1099-1111.

Examples


n <- 5000
X <- rtvAR1(n, sigma = 0.93)
plot(X)


ssaBSS documentation built on Dec. 1, 2022, 5:07 p.m.