apply_normalNB: Apply the algorithms to make decisions for Thompson sampling...
In countts: Thomson Sampling for Zero-Inflated Count Outcomes
apply_normalNB R Documentation
Apply the algorithms to make decisions for Thompson sampling Negative Binomial (TS-NB) algorithms
Description
Apply the algorithms to make decisions for Thompson sampling Negative Binomial (TS-NB) algorithms
Usage
apply_normalNB(context, beta_normalNB)
Arguments
context
context at the current decision time
beta_normalNB
the randomly sampled Bayesian estimate
Value
Intervention option
Examples
apply_normalNB(matrix(1:10, nrow = 2),matrix(11:20, nrow = 5))
countts documentation built on May 29, 2024, 10:23 a.m.
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| apply_normalNB | R Documentation |
Apply the algorithms to make decisions for Thompson sampling Negative Binomial (TS-NB) algorithms
Description
Apply the algorithms to make decisions for Thompson sampling Negative Binomial (TS-NB) algorithms
Usage
apply_normalNB(context, beta_normalNB)
Arguments
context |
context at the current decision time |
beta_normalNB |
the randomly sampled Bayesian estimate |
Value
Intervention option
Examples
apply_normalNB(matrix(1:10, nrow = 2),matrix(11:20, nrow = 5))
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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