distrib_diff_lcwm {outlierMBC} | R Documentation |
Compute the dissimilarity for a linear cluster-weighted model and identify the lowest density observation.
Description
At each iteration of ombc_lcwm, distrib_diff_lcwm
computes the
dissimilarity value of the current linear cluster-weighted model. It also
identifies the observation with the lowest mixture density.
Usage
distrib_diff_lcwm(x, z, prop, mu, sigma, mod_list, y_sigma, dd_weight = 0.5)
Arguments
x |
Covariate data only. |
z |
Component assignment probability matrix. |
prop |
Vector of component proportions. |
mu |
Matrix of component mean vectors. |
sigma |
Array of component covariance matrices. |
mod_list |
List of component regression models. |
y_sigma |
Vector of component regression standard deviations. |
dd_weight |
A value between |
Value
distrib_diff_lcwm_lcwm
returns a list with the following elements:
distrib_diff
Aggregated dissimilarity across components.
distrib_diff_vec
Vector containing dissimilarity value for each component.
choice_id
Index of observation with lowest mixture density.
removal_dens
Value of the lowest mixture density.
distrib_diff_mat
Two-column matrix containing response and covariate dissimilarities across components.