Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1152044 | Statistics & Probability Letters | 2013 | 7 Pages |
Abstract
Fisher’s linear discriminant function might be difficult to estimate, when data come from a semiparametric, finite mixture model. We propose an estimator based on the singular value decomposition of the third standardized cumulant. The estimator is consistent when sampling from a mixture of two symmetric, homoscedastic components with finite third moments and different weights. We also evaluate its performance and compare it with another estimator, which uses the eigenvectors of a kurtosis matrix.
Related Topics
Physical Sciences and Engineering
Mathematics
Statistics and Probability
Authors
Nicola Loperfido,