There are well established strategies for measuring fuel poverty in developed countries based on heating factors correlated with household income (expenditure, restriction or cold houses), but they do not translate to tropical regions where climatic conditions and socioeconomic contexts entail different energy use. Fuel has never been defined. We propose a new framework the identification of fu...

introduction: in recent years, most environmental evaluation studies have managed the heterogeneity of preferences among individuals. differing sensitivities are the basis for targeted communication programs and promotions. as consumer preferences and sensitivities become more diverse, it becomes less and less efficient to consider the society in the aggregate. in this research, we will show ho...

This article discusses a latent variable model for inference and prediction of symmetric relational data. The model, based on the idea of the eigenvalue decomposition, represents the relationship between two nodes as the weighted inner-product of node-specific vectors of latent characteristics. This “eigenmodel” generalizes other popular latent variable models, such as latent class and distance...

Summary Usually in latent class (LC) analysis, external predictors are taken to be cluster conditional probability (LC models with predictors), and/or score regression models). In such cases, their distribution is not of interest. Class‐specific interest the distal outcome model, when variables assumed depend on LC membership. this paper, we consider a more general formulation, that embeds both...

This article uses latent structure analysis to model ordered category ratings by multiple experts on the appropriateness of indications for the medical procedure carotid endarterectomy. The statistical method used is a form of located latent class analysis, which combines elements of latent class and latent trait analysis. It assumes that treatment indications fall into distinct latent classes,...

Finite mixture models, which are a type of latent variable model, express the overall distribution of one or more variables as a mixture of a finite number of component distributions. In direct applications, one assumes that the overall population heterogeneity with respect to a set of manifest variables results from the existence of two or more distinct homogeneous subgroups, or latent classes...

Latent class models are increasingly used to assess the accuracy of medical diagnostic tests and other classifications when no gold standard is available and the true state is unknown. When the latent class is treated as the true class, the latent class models provide measures of components of accuracy including specificity and sensitivity and their complements, type I and type II error rates. ...