simulated_piecewise: Simulated Piecewise Time Series Dataset

In BayesSpec: Bayesian Spectral Analysis Techniques

Description

This dataset is simulated from a piecewise autoregressive process (model (11), p. 1581, in Rosen et al. (2012)), see Examples.

Usage

data(simulated_piecewise)

Format

A univariate numeric vector with 1,024 observations.

Source

Simulated

References

Rosen, O., Wood, S. and Stoffer, D. (2012). AdaptSPEC: Adaptive Spectral Estimation for Nonstationary Time Series. J. of the American Statistical Association, 107, 1575-1589

Examples

#Created using the following script:
set.seed(346)
phi_true <- matrix(list(),3,1)
phi_true[[1]] <- .9
phi_true[[2]] <- c(1.69, -.81)
phi_true[[3]] <- c(1.32, -.81)
sd_true <- rep(1,3)
x1 <- arima.sim(list(order=c(1,0,0), ar=phi_true[[1]]),512,sd=sd_true[1])
x2 <- arima.sim(list(order=c(2,0,0), ar=phi_true[[2]]),256,sd=sd_true[2])
x3 <- arima.sim(list(order=c(2,0,0), ar=phi_true[[3]]),256,sd=sd_true[3])
simulated_piecewise <- c(x1, x2, x3)
plot.ts(simulated_piecewise)

Example output

Bayesian Spectral Analysis

Sally Cripps & Ori Rosen

Centre for Translational Data Science

Sydney Informatics Hub

BayesSpec documentation built on May 2, 2019, 2:44 a.m.