This learner fits first harmonics in a Fourier expansion to one
or more time series. Fourier decomposition relies on
fourier
, and the time series is fit using
tslm
Lrnr_HarmonicReg
R6Class
object.
Learner object with methods for training and prediction. See
Lrnr_base
for documentation on learners.
Kparam
Maximum order of the fourier terms. Passed to
fourier
.
n.ahead=NULL
The forecast horizon. If not specified, returns
forecast of size task$X
.
freq
The frequency of the time series.
...
Not used.
Other Learners: Custom_chain
,
Lrnr_arima
, Lrnr_bartMachine
,
Lrnr_base
, Lrnr_bilstm
,
Lrnr_condensier
, Lrnr_cv
,
Lrnr_define_interactions
,
Lrnr_expSmooth
,
Lrnr_glm_fast
, Lrnr_glmnet
,
Lrnr_glm
, Lrnr_h2o_grid
,
Lrnr_hal9001
,
Lrnr_independent_binomial
,
Lrnr_lstm
, Lrnr_mean
,
Lrnr_nnls
, Lrnr_optim
,
Lrnr_pca
,
Lrnr_pkg_SuperLearner
,
Lrnr_randomForest
,
Lrnr_ranger
, Lrnr_rpart
,
Lrnr_rugarch
, Lrnr_sl
,
Lrnr_solnp_density
,
Lrnr_solnp
,
Lrnr_subset_covariates
,
Lrnr_svm
, Lrnr_tsDyn
,
Lrnr_xgboost
, Pipeline
,
Stack
, define_h2o_X
,
undocumented_learner