random_walk: Metropolis sampling of a discrete distribution
In bayesball/TeachBayes: Teaching Bayesian Inference
Description
Usage
Arguments
Value
Author(s)
Description
Implements Metropolis sampling for an arbitrary discrete probability distribution
Usage
1
random_walk(pd, start, num_steps)
Arguments
pd
function containing discrete probability function on the integers 1, 2, ...
start
starting value of algorithm
num_steps
number of iterations of algorithm
Value
A vector of simulated values
Author(s)
Jim Albert
bayesball/TeachBayes documentation built on Jan. 5, 2020, 1:47 a.m.
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Description Usage Arguments Value Author(s)
Description
Implements Metropolis sampling for an arbitrary discrete probability distribution
Usage
1 | random_walk(pd, start, num_steps)
|
Arguments
pd |
function containing discrete probability function on the integers 1, 2, ... |
start |
starting value of algorithm |
num_steps |
number of iterations of algorithm |
Value
A vector of simulated values
Author(s)
Jim Albert
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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