SBAGM (version 0.1.0)

ARIMAAIC: Find the appropriate ARIMA model

Description

Computes the AIC values of all possible ARIMA models for the given value of autoregressive and moving average parameters.

Usage

ARIMAAIC(data, p=3, q=3, d=0, season=list(order=c(0,0,0),period=NA),
in.mean=TRUE)

Arguments

data

Univariate time series data

p

Non-seasonal autoregressive order

q

Non-seasonal moving average order

d

Degree of differencing

season

A specification of the seasonal part of the ARIMA model, plus the period. This should be a list with components order and period.

in.mean

Should the ARMA model include a mean/intercept term? The default is TRUE for undifferenced series, and it is ignored for ARIMA models with differencing.

Value

aic_mat

AIC values of all possible ARIMA models

Details

Lower the AIC value better the model

References

Box, G. and Jenkins, G. (1970). Time Series Analysis: Forecasting and Control. Holden-Day, San Francisco.

Brockwell, P. J. and Davis, R. A. (1996). Introduction to Time Series and Forecasting. Springer, New York. Sections 3.3 and 8.3.

Examples

# NOT RUN {
data("ReturnSeries")
ARIMAAIC(ReturnSeries)
# }