naive_params: Tuning Parameters for Random Walk Models
In bayesmodels: The 'Tidymodels' Extension for Bayesian Models
Description
Usage
Details
Value
Description
Tuning Parameters for Random Walk Models
Usage
1
Details
The main parameters for Random Walk Models are:
-
seasonal_random_walk: A boolean value for select a seasonal random walk instead.
-
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
bayesmodels documentation built on June 29, 2021, 1:06 a.m.
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Description Usage Details Value
Description
Tuning Parameters for Random Walk Models
Usage
1 |
Details
The main parameters for Random Walk Models are:
-
seasonal_random_walk: A boolean value for select a seasonal random walk instead. -
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
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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