gen.gts: Create a GMWM TS Object based on model

Description

Create a gts object based on a supplied time series model.

Usage

gen.gts(model, N = 1000, start = 0, end = NULL, freq = 1, unit = NULL, name = NULL)

Arguments

model

A ts.model or gmwm object containing one of the allowed models.

An interger containing the amount of observations for the time series.

start

A numeric that provides the time of the first observation.

end

A numeric that provides the time of the last observation.

freq

A numeric that provides the rate of samples. Default value is 1.

unit

A string that contains the unit expression of the frequency. Default value is NULL.

name

A string that provides an identifier to the data. Default value is NULL.

Value

A gts object with the following attributes:

start: The time of the first observation
end: The time of the last observation
freq: Numeric representation of frequency
unit: String representation of the unit
name: Name of the dataset

Details

This function accepts either a ts.model object (e.g. AR1(phi = .3, sigma2 =1) + WN(sigma2 = 1)) or a gmwm object.

Examples

Run this code

# Set seed for reproducibility
set.seed(1336)

n = 1000

# AR1 + WN
model = AR1(phi = .5, sigma2 = .1) + WN(sigma2=1)
x = gen.gts(model, n)
x
plot(x)

set.seed(1336)
# GM + WN
# Convert from AR1 to GM values
m = ar1_to_gm(c(.5,.1),10)
# Beta = 6.9314718, Sigma2_gm = 0.1333333
model = GM(beta = m[1], sigma2_gm = m[2]) + WN(sigma2=1)
x2 = gen.gts(model, n, freq = 10, unit = 'sec')
x2

plot(x2, to.unit = 'min')

# Same time series
all.equal(x, x2, check.attributes = FALSE)