SARMA: Create a Seasonal Autoregressive Moving Average (SARMA)...

In SMAC-Group/simts: Time Series Analysis Tools

Create a Seasonal Autoregressive Moving Average (SARMA) Process

Description

Sets up the necessary backend for the SARMA process.

Usage

SARMA(ar = 1, ma = 1, sar = 1, sma = 1, s = 12, sigma2 = 1)

Arguments

ar	A vector or integer containing either the coefficients for \phi's or the process number p for the Autoregressive (AR) term.
ma	A vector or integer containing either the coefficients for \theta's or the process number q for the Moving Average (MA) term.
sar	A vector or integer containing either the coefficients for \Phi's or the process number P for the Seasonal Autoregressive (SAR) term.
sma	A vector or integer containing either the coefficients for \Theta's or the process number Q for the Seasonal Moving Average (SMA) term.
s	A integer indicating the seasonal value of the data.
sigma2	A double value for the standard deviation, \sigma, of the SARMA process.

Details

A variance is required since the model generation statements utilize randomization functions expecting a variance instead of a standard deviation unlike R.

Value

An S3 object with called ts.model with the following structure:

process.desc

AR*p, MA*q, SAR*P, SMA*Q

theta

\sigma

plength

Number of Parameters

print

String containing simplified model

obj.desc

y desc replicated x times

obj

Depth of Parameters e.g. list(c(length(ar), length(ma), length(sar), length(sma), 1) )

starting

Guess Starting values? TRUE or FALSE (e.g. specified value)

Author(s)

James Balamuta

Examples

# Create an SARMA(1,2)x(1,1) process
SARMA(ar = 1, ma = 2,sar = 1, sma =1)

# Creates an SARMA(1,1)x(1,1) process with predefined coefficients.
SARMA(ar=0.23, ma=0.4, sar = .3, sma = .3)

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