ts.data.generator: Time Series Data Generator

In gnardin/stationarity: Time Series Stationarity Test

Description

Generates stationary or non-stationary time series data with mean or variance trend and different error distributions.

Usage

ts.data.generator(TS, y0, delta, tau, phi, theta, error, omega, burnin,
  continue)

Arguments

TS	Size of the time series
y0	Y[0] value
delta	Drift constant
tau	Trend on the mean
phi	Matrix of autoregressive parameters over time
theta	Matrix of moving average parameters over time
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)
omega	Trend on the variance
burnin	Number of samples thrown away at the beginning of time series generation
continue	Continues a previous time series (Supports only AR(1) and NO MOVING AVERAGE)

Value

Time series of size N

Examples

x <- 100
ts.data.generator(x, 0, 0, 0, 1, 0, c(ERROR_N,0,1), 0, 10, TRUE)

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