rls_prm {onlineforecast} | R Documentation |
Function for generating the parameters for RLS regression
Description
Function for generating the parameters for RLS regression
Usage
rls_prm(lambda)
Arguments
lambda |
The forgetting factor |
Details
The RLS needs only a forgetting factor parameter.
Value
A list of the parameters
Examples
# Take data
D <- subset(Dbuilding, c("2010-12-15", "2011-01-01"))
D$y <- D$heatload
D$scoreperiod <- in_range("2010-12-20", D$t)
# Define a simple model
model <- forecastmodel$new()
model$add_inputs(Ta = "Ta", mu = "one()")
model$kseq <- 1:6
# Here the expression which sets the parameters is defined
model$add_regprm("rls_prm(lambda=0.99)")
model$regprmexpr
# These will fit with lambda=0.99
rls_fit(prm=NA, model, D)
rls_fit(prm=c(lambda=0.99), model, D)
# The expression is evaluated when the model is fitted
rls_fit(prm=c(lambda=0.85), model, D)
# What happens is simply that the expression was manipulated
model$regprmexpr
model$regprm
# Same change could be done by
model$regprm <- list(lambda=0.3)
model$regprm
val <- rls_fit(prm=NA, model, D)
[Package onlineforecast version 1.0.2 Index]