# arimaID: Automatic Modeling of a Scalar Time Series In SLBDD: Statistical Learning for Big Dependent Data

## Description

Automatic selection and estimation of a regular or possibly seasonal ARIMA model for a given time series.

## Usage

 ``` 1 2 3 4 5 6 7 8 9 10 11 12``` ```arimaID( zt, maxorder = c(5, 1, 3), criterion = "bic", period = c(12), output = TRUE, method = "CSS-ML", pv = 0.01, spv = 0.01, transpv = 0.05, nblock = 0 ) ```

## Arguments

 `zt` T by 1 vector of an observed scalar time series without any missing values. `maxorder` Maximum order of (p,d,q) where p is the AR order, d the degree of differencing, and q the MA order. Default value is (5,1,4). `criterion` Information criterion used for model selection. Either AIC or BIC. Default is "bic". `period` Seasonal period. Default value is 12. `output` If TRUE it returns the differencing order, the selected order and the minimum value of the criterion. Default is TRUE. `method` Estimation method. See the arima command in R. Possible values are "CSS-ML", "ML", and "CSS". Default is "CSS-ML". `pv` P-value for unit-root test. Default value is 0.01. `spv` P-value for detecting seasonality. Default value is 0.01. `transpv` P-value for checking non-linear transformation. Default value is 0.05. `nblock` Number of blocks used in checking non-linear transformations. Default value is floor(sqrt(T)).

## Details

The program follows the following steps:

• Check for seasonality: fitting a multiplicative ARIMA(p,0,0)(1,0,0)_s model to a scalar time series and testing if the estimated seasonal AR coefficient is significant.

• Check for non-linear transformation: the series is divided into a given number of consecutive blocks and in each of them the Mean Absolute Deviation (MAD) and the median is computed. A regression of the log of the MAD with respect to the log of the median is run and the slope defines the non-linear transformation.

• Select orders: maximum order of (p,d,q).

## Value

A list containing:

• data - The time series. If any non-linear transformation is taken, "data" is the transformed series.

• order - Regular ARIMA order.

• sorder - Seasonal ARIMA order.

• period - Seasonal period.

• include.mean - Switch concerning the inclusion of mean in the model.

## Examples

 ```1 2``` ```data(TaiwanAirBox032017) fit <- arimaID(TaiwanAirBox032017[,1]) ```

SLBDD documentation built on March 27, 2021, 9:07 a.m.