| ARIMAAIC {SBAGM} | R Documentation |
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. |
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)