SampleCluster: Posterior samples of cluster assignments and Prior parameters
In microclustr: Entity Resolution with Random Partition Priors for Microclustering
Description
Usage
Arguments
Value
Description
Posterior samples of cluster assignments and Prior parameters
Usage
1
SampleCluster(data, Prior, burn, nsamples, spacing = 1000, block_flag = TRUE)
Arguments
data
Data frame containing only categorical variables
Prior
Specify partition prior: "DP", "PY", "ESCNB"
burn
MCMC burn-in period
nsamples
MCMC iterations after burn-in
spacing
Thinning for chaperones algorithm (default 1000)
block_flag
TRUE for non-uniform chaperones (default)
Value
List with posterior samples for cluster assignments (Z),
Prior parameters and distortion probabilities (Params)
microclustr documentation built on Jan. 13, 2021, 8:58 p.m.
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Description Usage Arguments Value
Description
Posterior samples of cluster assignments and Prior parameters
Usage
1 | SampleCluster(data, Prior, burn, nsamples, spacing = 1000, block_flag = TRUE)
|
Arguments
data |
Data frame containing only categorical variables |
Prior |
Specify partition prior: "DP", "PY", "ESCNB" |
burn |
MCMC burn-in period |
nsamples |
MCMC iterations after burn-in |
spacing |
Thinning for chaperones algorithm (default 1000) |
block_flag |
TRUE for non-uniform chaperones (default) |
Value
List with posterior samples for cluster assignments (Z), Prior parameters and distortion probabilities (Params)
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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