ts.break.autocorrelation: Time Series Data Generator with Break in the Autocorrelation

Description Usage Arguments Value Examples

Description

Generates non-stationary time series data with break in the autocorrelation and normal error distribution.

Usage

1
ts.break.autocorrelation(N, TS, delta, phis, thetas, error, seeds, burnin)

Arguments

N

Number of time series

TS

Size of the time series

delta

Mean

phis

Vector with two autoregressive values

thetas

Vector with two moving average values

error

Type of error and parameters Normal - c(ERROR_N, mean, stdv) Exponential - c(ERROR_E, mean, lambda) Triangle - c(ERROR_T, lower, upper, mode)

seeds

Vector of seeds

burnin

Number of samples thrown away at the beginning of time series generation

Value

N time series of size TS

Examples

1
2
ts.break.autocorrelation(5, 5000, 0, c(0.45, 0.9), c(0, 0), c(ERROR_N, 0, 1),
c(645,983,653,873,432), 10)

gnardin/stationarity documentation built on May 17, 2019, 7:29 a.m.