rlgt: Fit an Rlgt model

In Rlgt: Bayesian Exponential Smoothing Models with Trend Modifications

Fit an Rlgt model

Description

The main function to fit an rlgt model. It fits the parameter values with MCMC.

Usage

rlgt(
  y,
  seasonality = 1,
  seasonality2 = 1,
  seasonality.type = c("multiplicative", "generalized"),
  error.size.method = c("std", "innov"),
  level.method = c("HW", "seasAvg", "HW_sAvg"),
  xreg = NULL,
  control = rlgt.control(),
  verbose = FALSE,
  method = "Stan",
  experimental = "",
  homoscedastic = F
)

Arguments

y	time-series data for training (provided as a numeric vector, or a ts, or msts object).
seasonality	This specification of seasonality will be overridden by frequency of y, if y is of ts or msts class. 1 by default, i.e. no seasonality.
seasonality2	Second seasonality. If larger than 1, a dual seasonality model will be used. However, this is experimental. If not specified and multiple seasonality time series (of msts class) is used, a single seasonality model will be applied, one with seasonality equal to the largest of seasonalities of the time series. 1 by default, i.e. no seasonality or single seasonality.
seasonality.type	Either "multiplicative" (default) or "generalized". The latter seasonality generalizes additive and multiplicative seasonality types.
error.size.method	Function providing size of the error. Either "std" (monotonically, but slower than proportionally, growing with the series values) or "innov" (proportional to a smoothed abs size of innovations, i.e. surprises)
level.method	"HW", "seasAvg", "HW_sAvg". Here, "HW" follows Holt-Winters approach. "seasAvg" calculates level as a smoothed average of the last seasonality number of points (or seasonality2 of them for the dual seasonality model), and HW_sAvg is an weighted average of HW and seasAvg methods.
xreg	Optionally, a vector or matrix of external regressors, which must have the same number of rows as y.
control	list of control parameters, e.g. hyperparameter values for the model's prior distributions, number of fitting interations etc.
verbose	whether verbose information should be printed (Boolean value only), default FALSE.
method	Sampling method, default Stan.
experimental	Run different versions ("nostudent", "noglobal", "nohet", "ets") for ablation studies
homoscedastic	Run with homoscedastic or heteroscedastic version of the Gibbs sampler version. By default it is set to FALSE, i.e., run a heteroscedastic model.

Value

rlgtfit object

Examples

# The following is a toy example that runs within a few seconds. To get good 
# fitting results the number of iterations should be set to at least 2000, and 
# 4 chains should be used (the default). To speed up computation the number of 
# cores should also be adjusted (default is 4).

rlgt_model <- rlgt(lynx, 
       control=rlgt.control(MAX_NUM_OF_REPEATS=1, NUM_OF_ITER=50, NUM_OF_CHAINS = 1, 
                            NUM_OF_CORES = 1), verbose=TRUE)

# print the model details
print(rlgt_model)

## Not run: demo(exampleScript)

Rlgt documentation built on Sept. 11, 2024, 7:49 p.m.