sSummaryModel: Collects All Models Specified by "sarimaSpec"

In SLBDD: Statistical Learning for Big Dependent Data

Collects All Models Specified by "sarimaSpec"

Description

Models specified by "sarimaSpec".

Usage

sSummaryModel(
  x,
  maxorder = c(3, 1, 2),
  period = 12,
  criterion = "bic",
  method = "CSS"
)

Arguments

x	T by k data matrix: T data points in rows with each row being data at a given time point, and k time series in columns.
maxorder	Maximum order of ARIMA model (p,d,q) where p is the AR order, d the degree of differencing, and q the MA order. Default value is (3,1,2).
period	Seasonal period. The default is 12.
criterion	Information criterion used for model selection. Either AIC or BIC. Default is "bic".
method	Estimation method. See the arima command in R. Possible values are "CSS-ML", "ML", and "CSS". Default is "CSS".

Value

A list containing:

• Order - Order of ARIMA model (p, d, q, P, D, Q) of each series. A matrix of (ncol(x),6). The six columns are "p","d","q", "P", "D", "Q".

• Mean - A logical vector indicating whether each series needs a constant (or mean).

• M1 - Contains orders the stationary series.

• M2 - Contains orders of series with (d=1) and (D=0).

• M3 - Contains orders of series with (d=2) and (D=0).

• M4 - Contains orders of series with (d=0) and (D=1).

• M5 - Contains orders of series with (d=1) and (D=1).

• M6 - Contains orders of series with (d=2) and (D=1).

Examples

data(TaiwanAirBox032017)
summary <- sSummaryModel(TaiwanAirBox032017[,1:3])

SLBDD documentation built on April 27, 2022, 5:08 p.m.