bayesmodels (version 0.1.1)

ssm_params: Tuning Parameters for Additive Linear State Space Regression Models

Description

Tuning Parameters for Additive Linear State Space Regression Models

Usage

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

# NOT RUN {
damped_model()

seasonal_model()


# }