This learner supports prediction using hierarchical time-series modeling,
using hts. Fitting is done with `hts`

and prediction
is performed via `forecast.gts`

.

`R6Class`

object.

Learner object with methods for training and prediction. See
`Lrnr_base`

for documentation on learners.

`method)`

Method for distributing forecasts within hierarchy. See details of

`forecast.gts`

.`weights)`

Weights used for "optimal combination" method:

`weights="ols"`

uses an unweighted combination (as described in Hyndman et al 2011);`weights="wls"`

uses weights based on forecast variances (as described in Hyndman et al 2015);`weights="mint"`

uses a full covariance estimate to determine the weights (as described in Hyndman et al 2016);`weights="nseries"`

uses weights based on the number of series aggregated at each node.`fmethod)`

Forecasting method to use for each series.

`algorithms)`

An algorithm to be used for computing the combination forecasts (when

`method=="comb"`

). The combination forecasts are based on an ill-conditioned regression model. "lu" indicates LU decomposition is used; "cg" indicates a conjugate gradient method; "chol" corresponds to a Cholesky decomposition; "recursive" indicates the recursive hierarchical algorithm of Hyndman et al (2015); "slm" uses sparse linear regression. Note that`algorithms = "recursive"`

and`algorithms = "slm"`

cannot be used if`weights="mint"`

.`covariance)`

Type of the covariance matrix to be used with

`weights="mint"`

: either a shrinkage estimator ("shr") with shrinkage towards the diagonal; or a sample covariance matrix ("sam").`keep.fitted)`

If

`TRUE`

, keep fitted values at the bottom level.`keep.resid)`

If

`TRUE`

, keep residuals at the bottom level.`positive)`

If

`TRUE`

, forecasts are forced to be strictly positive (by setting`lambda=0`

).`lambda)`

Box-Cox transformation parameter.

`level`

Level used for "middle-out" method (only used when

`method = "mo"`

).`parallel`

If

`TRUE`

, import parallel to allow parallel processing.`num.cores`

If

`parallel = TRUE`

, specify how many cores are going to be used.

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