Tuning Parameters for Additive Linear State Space Regression Models

Source: R/dials-ssm_params.R

Tuning Parameters for Additive Linear State Space Regression Models

trend_model()

damped_model()

seasonal_model()

Value

A parameter

A parameter

A parameter

Details

The main parameters for Additive Linear State Space Regression Models are:

  • trend_model: A boolean value to specify a trend local level model.

  • damped_model: A boolean value to specify a damped trend local level model.

  • seasonal_model: A boolean value to specify a seasonal trend local level model.

  • markov_chains: The number of markov chains.

  • adapt_delta: The thin of the jumps in a HMC method

  • tree_depth: Maximum depth of the trees

Examples

trend_model()

#> a boolean value to specify a trend local level model.  (qualitative)
#> 2 possible value include:
#> FALSE and TRUE 

damped_model()

#> a boolean value to specify a damped trend local level model.  (qualitative)
#> 2 possible value include:
#> FALSE and TRUE 

seasonal_model()

#> a boolean value to specify a seasonal trend local level model.  (qualitative)
#> 2 possible value include:
#> FALSE and TRUE