estimate: Fit a Time Series Model to Data

In SMAC-Group/simts: Time Series Analysis Tools

Fit a Time Series Model to Data

Description

This function can fit a time series model to data using different methods.

Usage

estimate(model, Xt, method = "mle", demean = TRUE)

Arguments

model	A time series model.
Xt	A vector of time series data.
method	A string indicating the method used for model fitting. Supported methods include mle, yule-walker, gmwm and rgmwm.
demean	A boolean indicating whether the model includes a mean / intercept term or not.

Author(s)

Stéphane Guerrier and Yuming Zhang

Examples

Xt = gen_gts(300, AR(phi = c(0, 0, 0.8), sigma2 = 1))
plot(Xt)
estimate(AR(3), Xt)

Xt = gen_gts(300, MA(theta = 0.5, sigma2 = 1))
plot(Xt)
estimate(MA(1), Xt, method = "gmwm")

Xt = gen_gts(300, ARMA(ar = c(0.8, -0.5), ma = 0.5, sigma2 = 1))
plot(Xt)
estimate(ARMA(2,1), Xt, method = "rgmwm")

Xt = gen_gts(300, ARIMA(ar = c(0.8, -0.5), i = 1, ma = 0.5, sigma2 = 1))
plot(Xt)
estimate(ARIMA(2,1,1), Xt, method = "mle")

Xt = gen_gts(1000, SARIMA(ar = c(0.5, -0.25), i = 0, ma = 0.5, sar = -0.8, 
si = 1, sma = 0.25, s = 24, sigma2 = 1))
plot(Xt)
estimate(SARIMA(ar = 2, i = 0, ma = 1, sar = 1, si = 1, sma = 1, s = 24), Xt, 
method = "rgmwm")

SMAC-Group/simts documentation built on Sept. 4, 2023, 5:25 a.m.