ARIMAAIC: Find the appropriate ARIMA model

In SBAGM: Search Best ARIMA, GARCH, and MS-GARCH 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.

Details

Lower the AIC value better the model

Value

aic_mat

AIC values of all possible ARIMA models

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

data("ReturnSeries")
ARIMAAIC(ReturnSeries)

Example output

         q=0      q=1      q=2
p=0 589.7871 580.4268 582.3384
p=1 583.7818 582.3819 584.0126
p=2 580.7977 582.7494 583.9000

SBAGM documentation built on Oct. 28, 2020, 9:07 a.m.