R: Estimate Posterior Clustering Assignments

estimate_clustering_vi {SANvi}

R Documentation

Estimate Posterior Clustering Assignments

Description

This function estimates posterior clustering assignments based on posterior variational estimates obtained from one of the model implemented in SANvi.

Usage

estimate_clustering_vi(output, ordered = TRUE)

## S3 method for class 'vi_clustering'
plot(
  x,
  DC_num = NULL,
  type = c("ecdf", "boxplot", "scatter"),
  palette_brewed = FALSE,
  ...
)

## S3 method for class 'vi_clustering'
print(x, ...)

Arguments

`output`	an object of class `SANvb`, the output of one of the variational functions `variational_CAM`, `variational_fiSAN`, `variational_fSAN`.
`ordered`	logical, if `TRUE` (default), the function sorts the distributional cluster labels reflecting the increasing values of medians of the data assigned to each DC.
`x`	an object of class `variational_estimates`, which can be obtained from the function `estimate_atoms_weights_vi`.
`DC_num`	an integer or a vector of integers indicating which distributional clusters to plot.
`type`	what type of plot should be drawn (only for the left-side plot). Possible types are "boxplot", "ecdf", and "scatter".
`palette_brewed`	(logical) the color palette to be used. Default is `R` base colors (`palette_brewed = FALSE`).
`...`	ignored.

Value

a list of class clustering containing

obs_level: a data frame containing the data values, their group indexes, the observational and distributional clustering assignments for each observation.
dis_level: a vector with the distributional clustering assignment for each unit.

Examples


# Generate example data
set.seed(123)
y <- c(rnorm(100),rnorm(100,-5),rnorm(100,5),rnorm(100),
       rnorm(100),rnorm(100,-5),rnorm(100,5),rnorm(100))
g <- rep(1:4,rep(200,4))

# Fitting fiSAN via variational inference
est <- SANvi::variational_fiSAN(y,g,verbose = FALSE)

# Estimate clustering assignments
estimate_clustering_vi(est)