The goal of this study was to determine whether statistical modeling of population data for a phenotypic marker could reflect a major locus gene defect. Identifying mutations in the HFE gene makes it possible to assess the association between transferrin saturation (TS) subpopulations and HFE mutations. Data were analyzed from 27 895 white patients who attended a health appraisal clinic and who...

A robust estimation procedure for mixture linear regression models is proposed by assuming that the error terms follow a Laplace distribution. The estimation procedure is implemented by an EM algorithm based on the fact that the Laplace distribution is a scale mixture of a normal distribution. Finite sample performance of the proposed algorithm is evaluated by numerical simulation studies. The ...

We attempt to identify the number of underlying physical phenomena behind tomato lateral root initiation by using a normal mixture distribution coupled with the Box-Cox power transformation. An initial analysis of the data suggested the possibility of two (possibly more) subpopulations, but upon taking reciprocals, the data appear to be very nearly Gaussian. A simulation study explores the poss...

Estimating the distribution of impervious surface, a major component of the vegetation–impervious surface–soil (V–I–S) model, is important in monitoring urban areas and understanding human activities. Besides its applications in physical geography, such as run-off models and urban change studies, maps showing impervious surface distribution are essential for estimating socio-economic factors, s...

This paper presents convergence results for the Box Gaussian Mixture Filter (BGMF). BGMF is a Gaussian Mixture Filter (GMF) that is based on a bank of Extended Kalman Filters. The critical part of GMF is the approximation of probability density function (pdf) as pdf of Gaussian mixture such that its components have small enough covariance matrices. Because GMF approximates prior and posterior a...

Binary response regression is a useful technique for analyzing categorical data. Popular binary models use special link functions such as the logit or the probit link. In this article, the inverse link function H is modeled to be a scale mixture of cumulative distribution functions. Two different models for H are proposed: (i) H is a finite normal scale mixture with a Dirichlet distribution pri...

We investigate micelle formation in a system containing two or more different amphiphiles with different geometries using a stochastic molecular-dynamics (MD) simulation method. For a binary system containing two amphiphiles, we calculate the critical micelle concentration (CMC) and cluster distribution for the mixture at several mole fractions and compare the simulation results with those pred...

A method for probability density function (PDF) estimation using Bayesian mixtures of weighted gamma distributions, called the Dirichlet process gamma mixture model (DP-GaMM), is presented and applied to the analysis of a laser beam in turbulence. The problem is cast in a Bayesian setting, with the mixture model itself treated as random process. A stick-breaking interpretation of the Dirichlet ...

In most Information Retrieval (IR) applications, Euclidean distance is used for similarity measurement. It is adequate in many cases but this distance metric is not very accurate when there exist some different local data distributions in the database. We propose a Gaussian mixture distance for performing accurate nearest-neighbor search for Information Retrieval (IR). Under an established Gaus...