cluster_datapoints {nonparametric.bayes}

Gibbs sampling for the Chinese Restaurant Process Implementation details can be found in the associated paper The algorithm stops at every 1000th iteration and prints the current cluster configuration.

Description

Gibbs sampling for the Chinese Restaurant Process Implementation details can be found in the associated paper The algorithm stops at every 1000th iteration and prints the current cluster configuration.

Usage

cluster_datapoints(
  data,
  sd = 1,
  initialisation = rep(1, nrow(data)),
  sigma0 = matrix(c(1, 0, 0, 1), nrow = 2, byrow = TRUE)
)

Arguments

data

A matrix of nx2 containing the datapoints

sd

Prior standard deviation

initialisation

Cluster initialisation for each datapoint. Default initialisation is to set every point in the same cluster.

sigma0

Covariance matrix for the points. Default initialisation is set to matrix(c(1, 0, 0, 1), mrow=2, byrow=TRUE)

Value

Returns the cluster assignments after the last iteration. Examples cluster_datapoints(generate_split_data(350, 0.5)$x, sigma0=diag(3^2, 2)) cluster_datapoints(petal, sigma0=petal_sigma0) cluster_datapoints(width, sigma0=width_sigma0) cluster_datapoints(mixed, sigma0=mixed_sigma0)