forecast.rlgtfit: Rlgt forecast

In Rlgt: Bayesian Exponential Smoothing Models with Trend Modifications

Rlgt forecast

Description

produce forecasts from an rlgtfit object

Usage

## S3 method for class 'rlgtfit'
forecast(
  object,
  xreg = NULL,
  h = ifelse(frequency(object$x) > 1, 2 * frequency(object$x), 10),
  level = c(80, 95),
  NUM_OF_TRIALS = 2000,
  ...
)

Arguments

object	rlgtfit object
xreg	input regression matrix
h	forecasting horizon (the default is 10 for annual and 2*periods otherwise)
level	confidence levels for prediction intervals a.k.a. coverage percentiles. Musat be between 0 and 100.
NUM_OF_TRIALS	number of simulations to run. Suggested range is between (1000,5000), but it needs to be higher for good coverage for very high levels, e.g. 99.8.
...	currently not used

Value

returns a forecast object compatible with the forecast package in R

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)

# Produce Forecasts for the next 10 years
forecast_result <- forecast(rlgt_model, h = 10, level=c(80, 95, 98))

plot(forecast_result,main="Forecasting lynx dataset with LGT model")

Rlgt documentation built on Sept. 16, 2023, 1:08 a.m.