ssm_params: Tuning Parameters for Additive Linear State Space Regression...

In AlbertoAlmuinha/bayesmodels: The 'Tidymodels' Extension for Bayesian Models

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()

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

Value

A parameter

A parameter

A parameter

Examples

damped_model()

seasonal_model()

AlbertoAlmuinha/bayesmodels documentation built on Aug. 13, 2022, 1:45 p.m.