ts.trend.mean: Time Series Data Generator with Mean Trend

Description Usage Arguments Value Examples

Description

Generates non-stationary time series data with mean trend and normal error distribution.

Usage

1
ts.trend.mean(N, TS, delta, tau, phi, theta, error, seeds, burnin)

Arguments

N

Number of time series

TS

Size of the time series

delta

Mean

tau

Trend on the mean

phi

Vector of autoregressive parameters

theta

Vector of moving average parameters

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
ts.trend.mean(5, 5000, 0, 1, 0.9, 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.