Finite Mixture Estimation Algorithm for Arbitrary Function Approximation
نویسندگان
چکیده
منابع مشابه
Competitive EM algorithm for finite mixture models
In this paper, we present a novel competitive EM (CEM) algorithm for "nite mixture models to overcome the two main drawbacks of the EM algorithm: often getting trapped at local maxima and sometimes converging to the boundary of the parameter space. The proposed algorithm is capable of automatically choosing the clustering number and selecting the “split” or “merge” operations e7ciently based on...
متن کاملSimplifying mixture Models through Function Approximation Simplifying Mixture Models through Function Approximation
The finite mixture model is widely used in various statistical learning problems. However, the model obtained may contain a large number of components, making it inefficient in practical applications. In this paper, we propose to simplify the mixture model by first grouping similar components together and then performing local fitting through function approximation. By using the squared loss to...
متن کاملVector Quantization for Arbitrary Distance Function Estimation
| In this paper we apply the concepts of Vector Quantization (VQ) for the determination of arbitrary distance functions { a problem which has important applications in Logistics and Location Analysis. The input to our problem is the set of coordinates of a large number of nodes whose inter-node arbitrary \distances" have to be estimated. To render the problem interesting, non-trivial and realis...
متن کاملNonparametric Estimation of Finite-mixture Models
The aim of this paper is to provide simple nonparametric methods to estimate finite-mixture models from data with repeated measurements. Three measurements suffice for the mixtures to be fully identified and so our approach can be used even with very short panel data. We provide distribution theory for estimators of the number of mixture components, the mixing proportions, as well as of the mix...
متن کاملFinite 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 کاملذخیره 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: Strojniški vestnik – Journal of Mechanical Engineering
سال: 2012
ISSN: 0039-2480
DOI: 10.5545/sv-jme.2011.085