Theoretical grounding for estimation in conditional independence multivariate finite mixture models

Semi-Parametric Estimation for Conditional Independence Multivariate Finite Mixture Models

Abstract: The conditional independence assumption for nonparametric multivariate finite mixture models, a weaker form of the well-known conditional independence assumption for random effects models for longitudinal data, is the subject of an increasing number of theoretical and algorithmic developments in the statistical literature. After presenting a survey of this literature, including an in-...

Estimation for Conditional Independence Multivariate Finite Mixture Models

The conditional independence assumption for nonparametric multivariate finite mixture models may be considered to be a weaker form of the well-known conditional independence assumption for random effects models for longitudinal data. After summarizing important recent identifiability results, this article describes and extends an algorithm for estimation of the parameters in these models. The a...

Lattice Models for Conditional Independence in a Multivariate Normal Distribution

the application of multivariate probit models for conditional claim-types (the case study of iranian car insurance industry)

هدف اصلی نرخ گذاری بیمه ای تعیین نرخ عادلانه و منطقی از دیدگاه بیمه گر و بیمه گذار است. تعین نرخ یکی از مهم ترین مسایلی است که شرکتهای بیمه با آن روبرو هستند، زیرا تعیین نرخ اصلی ترین عامل در رقابت بین شرکتها است. برای تعیین حق بیمه ابتدا می باید مقدار مورد انتظار ادعای خسارت برای هر قرارداد بیمه را برآورد کرد. روش عمومی مدل سازی خسارتهای عملیاتی در نظر گرفتن تواتر و شدت خسارتها می باشد. اگر شر...

Learning mixture models – courseware for finite mixture models of multivariate Bernoulli distributions

Teaching of machine learning should aim at the readiness to understand and implement modern machine learning algorithms. Towards this goal, we often have course exercises involving the student to solve a practical machine learning problem involving a reallife data set. The students implement the programs of machine learning methods themselves and gain deep insight on the implementation details ...