Finite Mixture Modeling via REBMIX

نویسندگان

چکیده

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

rebmix: An R Package for Continuous and Discrete Finite Mixture Models

The rebmix package for R provides functions for random univariate and multivariate finite mixture generation, number of components, component weights and component parameters estimation, bootstrapping and plotting of the finite mixtures. It relies on the REBMIX algorithm that requires preprocessing, information criterion and conditionally independent normal, lognormal, Weibull, gamma, binomial,...

متن کامل

rebmix: The Rebmix Package

The rebmix package for fitting finite mixture models implemented in R package rebmix is presented. It provides functions for random univariate and multivariate finite mixture generation, the number of components, component weights and component parameter estimation, bootstrapping and the plotting of finite mixtures. It requires preprocessing of observations, information criterion and conditiona...

متن کامل

Multivariate normal mixture modeling, clustering and classification with the rebmix package

The rebmix package provides R functions for random univariate and multivariate finite mixture model generation, estimation, clustering and classification. The paper is focused on multivariate normal mixture models with unrestricted variance-covariance matrices. The objective is to show how to generate datasets for a known number of components, numbers of observations and component parameters, h...

متن کامل

Finite mixture modeling with mixture outcomes using the EM algorithm.

This paper discusses the analysis of an extended finite mixture model where the latent classes corresponding to the mixture components for one set of observed variables influence a second set of observed variables. The research is motivated by a repeated measurement study using a random coefficient model to assess the influence of latent growth trajectory class membership on the probability of ...

متن کامل

Sufficient dimension reduction via bayesian mixture modeling.

Dimension reduction is central to an analysis of data with many predictors. Sufficient dimension reduction aims to identify the smallest possible number of linear combinations of the predictors, called the sufficient predictors, that retain all of the information in the predictors about the response distribution. In this article, we propose a Bayesian solution for sufficient dimension reduction...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: Journal of Algorithms and Optimization

سال: 2015

ISSN: 2312-7767,2312-7759

DOI: 10.5963/jao0302001