Finite Mixture Distributions with Skew Normal Components
نویسنده
چکیده مقاله:
این مقاله چکیده ندارد
منابع مشابه
Determination of the number of components in finite mixture distribution with Skew-t-Normal components
Abstract One of the main goal in the mixture distributions is to determine the number of components. There are different methods for determination the number of components, for example, Greedy-EM algorithm which is based on adding a new component to the model until satisfied the best number of components. The second method is based on maximum entropy and finally the third method is based on non...
متن کاملSkew Laplace Finite Mixture Modelling
‎This paper presents a new mixture model via considering the univariate skew Laplace distribution‎. ‎The new model can handle both heavy tails and skewness and is multimodal‎. ‎Describing some properties of the proposed model‎, ‎we present a feasible EM algorithm for iteratively‎ ‎computing maximum likelihood estimates‎. ‎We also derive the observ...
متن کاملThe Family of Scale-Mixture of Skew-Normal Distributions and Its Application in Bayesian Nonlinear Regression Models
In previous studies on fitting non-linear regression models with the symmetric structure the normality is usually assumed in the analysis of data. This choice may be inappropriate when the distribution of residual terms is asymmetric. Recently, the family of scale-mixture of skew-normal distributions is the main concern of many researchers. This family includes several skewed and heavy-tailed d...
متن کاملMixture of Normal Mean-Variance of Lindley Distributions
‎Abstract: In this paper, a new mixture modelling using the normal mean-variance mixture of Lindley (NMVL) distribution has been considered. The proposed model is heavy-tailed and multimodal and can be used in dealing with asymmetric data in various theoretic and applied problems. We present a feasible computationally analytical EM algorithm for computing the maximum likelihood estimates. T...
متن کاملGrowth mixture modeling with non-normal distributions.
A limiting feature of previous work on growth mixture modeling is the assumption of normally distributed variables within each latent class. With strongly non-normal outcomes, this means that several latent classes are required to capture the observed variable distributions. Being able to relax the assumption of within-class normality has the advantage that a non-normal observed distribution do...
متن کاملFinite Mixture Models with Negative Components
Mixture models, especially mixtures of Gaussian, have been widely used due to their great flexibility and power. Non-Gaussian clusters can be approximated by several Gaussian components, however, it can not always acquire appropriate results. By cancelling the nonnegative constraint to mixture coefficients and introducing a new concept of “negative components”, we extend the traditional mixture...
متن کاملمنابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ذخیره در منابع من قبلا به منابع من ذحیره شده{@ msg_add @}
عنوان ژورنال
دوره 15 شماره 1
صفحات 3- 12
تاریخ انتشار 2010-09
با دنبال کردن یک ژورنال هنگامی که شماره جدید این ژورنال منتشر می شود به شما از طریق ایمیل اطلاع داده می شود.
کلمات کلیدی برای این مقاله ارائه نشده است
میزبانی شده توسط پلتفرم ابری doprax.com
copyright © 2015-2023