predict.srlTS

An implementation of sparsity-ranked lasso for
time series data. This methodology is especially useful for
large time series with exogenous features and/or complex
seasonality. Originally described in Peterson and Cavanaugh
(2022) <doi:10.1007/s10182-021-00431-7> in the context of variable
selection with interactions and/or polynomials, ranked sparsity is
a philosophy with methods useful for variable selection in the
presence of prior informational asymmetry. This situation exists for time
series data with complex seasonality, as shown in Peterson and Cavanaugh
(2023+) <doi:10.48550/arXiv.2211.01492>, which also describes this package
in greater detail. The Sparsity-Ranked Lasso (SRL) for Time Series
implemented in 'srlTS' can fit large/complex/high-frequency time series
quickly, even with a high-dimensional exogenous feature set. The SRL is
considerably faster than its competitors, while often producing more
accurate predictions. Also included is a long hourly series of arrivals
into the University of Iowa Emergency Department with concurrent local
temperature.

Ryan Andrew Peterson

srlTS

Sparsity-Ranked Lasso for Time Series

predict.srlTS function

<dl><dt>object</dt>
<dd>an srlTS object</dd>
<dt>n_ahead</dt>
<dd>number of times ahead to predict by iteration</dd>
<dt>X_test</dt>
<dd>a matrix exogenous features</dd>
<dt>y_test</dt>
<dd>the test series; needed for future predictions (optional; see
details)</dd>
<dt>cumulative</dt>
<dd>should cumulative (rolling) sums be returned (integer
indicating number of times to sum)</dd>
<dt>...</dt>
<dd>currently unused</dd></dl>

Arguments

Predict function for srlTS object — predict.srlTS

<dl>

<dt>object</dt>
<dd>an srlTS object</dd>


<dt>n_ahead</dt>
<dd>number of times ahead to predict by iteration</dd>


<dt>X_test</dt>
<dd>a matrix exogenous features</dd>


<dt>y_test</dt>
<dd>the test series; needed for future predictions (optional; see
details)</dd>


<dt>cumulative</dt>
<dd>should cumulative (rolling) sums be returned (integer
indicating number of times to sum)</dd>


<dt>...</dt>
<dd>currently unused</dd>

</dl>

predict.srlTS: Predict function for srlTS object

Description

Usage

Value

Arguments

Details

Examples