dynOAB: Dynamic programming of the optimal One-Armed Bandits
In mistat: Data Sets, Functions and Examples from the Book: "Modern Industrial Statistics" by Kenett, Zacks and Amberti
dynOAB R Documentation
Dynamic programming of the optimal One-Armed Bandits
Description
Dynamic programming of the optimal One-Armed Bernoulli Bandits process
Usage
dynOAB(N, al)
Arguments
N
number of trials.
al
the known probability of reward on arm A.
Value
For dynOAB the matrix of maximal predicted rewards.
For dynOAB2 the optimal predicted reward.
Author(s)
Shelemyahu Zacks
See Also
simOAB
Examples
dynOAB(10, 0.5)
dynOAB2(10, 0.5)
mistat documentation built on March 7, 2023, 6:43 p.m.
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| dynOAB | R Documentation |
Dynamic programming of the optimal One-Armed Bandits
Description
Dynamic programming of the optimal One-Armed Bernoulli Bandits process
Usage
dynOAB(N, al)
Arguments
N |
number of trials. |
al |
the known probability of reward on arm A. |
Value
For dynOAB the matrix of maximal predicted rewards. For dynOAB2 the optimal predicted reward.
Author(s)
Shelemyahu Zacks
See Also
simOAB
Examples
dynOAB(10, 0.5) dynOAB2(10, 0.5)
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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