rls_update: Updates the model fits

In onlineforecast: Forecast Modelling for Online Applications

Updates the model fits

Description

Calculates the RLS update of the model coefficients with the provived data.

Usage

rls_update(model, datatr = NA, y = NA, runcpp = TRUE)

Arguments

model	A model object
datatr	a data.list with transformed data (from model$transform_data(D))
y	A vector of the model output for the corresponding time steps in datatr
runcpp	Optional, default = TRUE. If TRUE, a c++ implementation of the update is run, otherwise a slower R implementation is used.

Details

See vignette ??ref(recursive updating, not yet finished) on how to use the function.

Value

Returns a named list for each horizon (model$kseq) containing the variables needed for the RLS fit (for each horizon, which is saved in model$Lfits):

It will update variables in the forecast model object.

See Also

See rls_predict.

Examples

# See rls_predict examples

onlineforecast documentation built on Oct. 12, 2023, 5:15 p.m.