distlat {MixSemiRob} | R Documentation |
Euclidean Distance Based Labeling Method for Label Switching
Description
‘distlat’ is used to address the label switching problem by minimizing the distance between the classification probabilities and the latent component label, which is the label used by the user to generate the sample (Yao, 2015). The function supports both one-dimensional (with equal variances or unequal variances) and multi-dimensional data (with equal variances).
Usage
distlat(est, lat)
Arguments
est |
a list with four elements representing the estimated mixture model,
which can be obtained using the |
lat |
a C by n zero-one matrix representing the latent component labels for all observations, where C is the number of components in the mixture model and n is the number of observations. If the (i, j)th cell is 1, it indicates that the jth observation belongs to the ith component. |
Value
The estimation results adjusted to account for potential label switching problems are returned, as a list containing the following elements:
mu |
C by p matrix of estimated component means. |
sigma |
C-dimensional vector of estimated component standard deviations (for univariate data) or p by p matrix of estimated component variance (for multivariate data). |
pi |
C-dimensional vector of estimated mixing proportions. |
References
Yao, W. (2015). Label switching and its solutions for frequentist mixture models. Journal of Statistical Computation and Simulation, 85(5), 1000-1012.
See Also
Examples
# See examples for the `complh' function.