forecast.ATA

Forecast a model from the fable ATA model

Allows ATA (Automatic Time series analysis using the Ata method) models from the 'ATAforecasting' package to be used in a tidy workflow with the modeling interface of
'fabletools'. This extends 'ATAforecasting' to provide enhanced model specification and management, performance evaluation methods, and
model combination tools. The Ata method (Yapar et al. (2019) <doi:10.15672/hujms.461032>), an alternative to exponential smoothing (described in Yapar (2016)
<doi:10.15672/HJMS.201614320580>, Yapar et al. (2017) <doi:10.15672/HJMS.2017.493>), is a new univariate time series forecasting method which provides
innovative solutions to issues faced during the initialization and optimization stages of existing forecasting methods.
Forecasting performance of the Ata method is superior to existing methods both in terms of easy implementation and accurate forecasting.
It can be applied to non-seasonal or seasonal time series which can be decomposed into four components (remainder, level, trend and seasonal).

Ali Sabri Taylan

fable.ata

'ATAforecasting' Modelling Interface for 'fable' Framework

Hanife Taylan Selamlar

Guckan Yapar

forecast.ATA function

<dl><dt>object</dt>
<dd>The time series model used to produce the forecasts</dd>
<dt>new_data</dt>
<dd>A `tsibble` containing future information used to forecast.</dd>
<dt>h</dt>
<dd>The forecast horison (can be used instead of `new_data` for regular time series with no exogenous regressors).</dd>
<dt>ci_level</dt>
<dd>Confidence Interval levels for forecasting. Default value is 95.</dd>
<dt>negative_forecast</dt>
<dd>Negative values are allowed for forecasting. Default value is TRUE. If FALSE, all negative values for forecasting are set to 0.</dd>
<dt>onestep</dt>
<dd>Default is FALSE. if TRUE, the dynamic forecast strategy uses a one-step model multiple times `h` forecast horizon) where the prediction for the prior time step is used as an input for making a prediction on the following time step.</dd>
<dt>...</dt>
<dd>Other arguments</dd></dl>

Arguments

Forecast a model from the fable ATA model — forecast.ATA

<dl>

<dt>object</dt>
<dd>The time series model used to produce the forecasts</dd>


<dt>new_data</dt>
<dd>A `tsibble` containing future information used to forecast.</dd>


<dt>h</dt>
<dd>The forecast horison (can be used instead of `new_data` for regular time series with no exogenous regressors).</dd>


<dt>ci_level</dt>
<dd>Confidence Interval levels for forecasting. Default value is 95.</dd>


<dt>negative_forecast</dt>
<dd>Negative values are allowed for forecasting. Default value is TRUE. If FALSE, all negative values for forecasting are set to 0.</dd>


<dt>onestep</dt>
<dd>Default is FALSE. if TRUE, the dynamic forecast strategy uses a one-step model multiple times `h` forecast horizon) where the prediction for the prior time step is used as an input for making a prediction on the following time step.</dd>


<dt>...</dt>
<dd>Other arguments</dd>

</dl>

forecast.ATA: Forecast a model from the fable ATA model

Description

Usage

Value

Arguments

Examples