Add to ORKGThis paper presents a finite mixture density which might be a potentially useful model for the clustering of mixed mode data. A simplex algorithm is used to obtain maximum likelihood estimates and several small scale numerical examples indicate that its performance is relatively satisfactory.finite mixtures clustering maximum likelihood estimation simplex algorith
This thesis deals with classification based on mixture models, mainly on models finite normal. At fi...
This work focuses on finite mixture models and aims to introduce the maximum likelihood method as an...
International audienceThe analysis of finite mixture models for exponential repeated data is conside...
The important role of finite mixture models in the statistical analysis of data is underscored by th...
The important role of finite mixture models in the statistical analysis of data is underscored by th...
Finite mixture models are being commonly used in a wide range of applications in practice concerning...
Cluster analysis via a finite mixture model approach is considered. With this approach to clustering...
In this paper, an algorithm is proposed to learn and evaluate different finite mixture models (FMMs)...
Finite mixture models are being increasingly used to model the distributions of a wide variety of ra...
Cluster analysis seeks to identify homogeneous subgroups of cases in a population. This article prov...
AbstractIn this paper, an algorithm is proposed to learn and evaluate different finite mixture model...
Finite Mixture models are a state-of-the-art technique of segmentation. Next tosegmenting consumers ...
Many of the methods which deal with clustering in matrices of data are based on mathematical techniq...
Clustering is a common and important issue, and finite mixture models based on the normal distributi...
AbstractThe analysis of finite mixture models for exponential repeated data is considered. The mixtu...
This thesis deals with classification based on mixture models, mainly on models finite normal. At fi...
This work focuses on finite mixture models and aims to introduce the maximum likelihood method as an...
International audienceThe analysis of finite mixture models for exponential repeated data is conside...
The important role of finite mixture models in the statistical analysis of data is underscored by th...
The important role of finite mixture models in the statistical analysis of data is underscored by th...
Finite mixture models are being commonly used in a wide range of applications in practice concerning...
Cluster analysis via a finite mixture model approach is considered. With this approach to clustering...
In this paper, an algorithm is proposed to learn and evaluate different finite mixture models (FMMs)...
Finite mixture models are being increasingly used to model the distributions of a wide variety of ra...
Cluster analysis seeks to identify homogeneous subgroups of cases in a population. This article prov...
AbstractIn this paper, an algorithm is proposed to learn and evaluate different finite mixture model...
Finite Mixture models are a state-of-the-art technique of segmentation. Next tosegmenting consumers ...
Many of the methods which deal with clustering in matrices of data are based on mathematical techniq...
Clustering is a common and important issue, and finite mixture models based on the normal distributi...
AbstractThe analysis of finite mixture models for exponential repeated data is considered. The mixtu...
This thesis deals with classification based on mixture models, mainly on models finite normal. At fi...
This work focuses on finite mixture models and aims to introduce the maximum likelihood method as an...
International audienceThe analysis of finite mixture models for exponential repeated data is conside...