simts (version 0.2.2)

SARMA: 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)

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)

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.

Author

James Balamuta

Details

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

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)