backtrack_gmm {outlierMBC}R Documentation

Fit a Gaussian mixture model to the backtrack solution.

Description

The backtrack function determines the number of outliers for the backtrack solution and plot_backtrack plots this on a dissimilarity curve. backtrack_gmm fits the mixture model corresponding to the number of outliers selected by the backtrack solution (or any manually specified number of outliers).

Usage

backtrack_gmm(
  x,
  ombc_out,
  max_total_rise = 0.1,
  max_step_rise = 0.05,
  init_model = NULL,
  init_z = NULL,
  manual_outlier_num = NULL,
  verbose = TRUE
)

Arguments

x

Data.

ombc_out

An "outliermbc_gmm" or "outliermbc_lcwm" object, i.e. an output from ombc_gmm or ombc_lcwm.

max_total_rise

Upper limit for the cumulative increase, as a proportion of the global minimum dissimilarity, from all backward steps.

max_step_rise

Upper limit for the increase, as a proportion of the global minimum dissimilarity, from each backward step.

init_model

Initial mixture model (mixture::gpcm best_model).

init_z

Initial component assignment probability matrix.

manual_outlier_num

User-specified number of outliers.

verbose

Whether the iteration count is printed.

Value

backtrack_gmm returns a list with the following elements:

labels

Vector of mixture component labels with outliers denoted by 0.

outlier_bool

Logical vector indicating if an observation has been classified as an outlier.

outlier_num

Number of observations classified as outliers.

mix

Output from mixture::gpcm fitted to the non-outlier observations.

call

Arguments / parameter values used in this function call.

Examples

ombc_gmm_k3n1000o10 <- ombc_gmm(
  gmm_k3n1000o10[, 1:2],
  comp_num = 3, max_out = 20
)

backtrack_gmm(gmm_k3n1000o10[, 1:2], ombc_gmm_k3n1000o10)

[Package outlierMBC version 0.0.1 Index]