Advances in Latent Variables: Methods, Models and by Maurizio Carpita, Eugenio Brentari, El Mostafa Qannari
By Maurizio Carpita, Eugenio Brentari, El Mostafa Qannari
The e-book, belonging to the sequence “Studies in Theoretical and utilized facts– chosen Papers from the Statistical Societies”, provides a peer-reviewed number of contributions on appropriate subject matters equipped via the editors at the party of the SIS 2013 Statistical convention "Advances in Latent Variables. equipment, types and Applications", held on the division of Economics and administration of the collage of Brescia from June 19 to 21, 2013.
The concentration of the e-book is on advances in statistical equipment for analyses with latent variables. in reality, lately, there was expanding curiosity during this wide learn zone from either a theoretical and an utilized viewpoint, because the statistical latent variable process permits the potent modeling of complicated real-life phenomena in quite a lot of study fields.
A significant aim of the amount is to assemble articles written through statisticians from varied study fields, which current diversified methods and stories relating to the research of unobservable variables and the research of the relationships among them.
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Extra info for Advances in Latent Variables: Methods, Models and Applications
As a consequence, the parameter cannot be strictly related to a dispersion aspect of the random variable. 1 / we get a regular increase over the whole parameter space and for any fixed . In fact, it is possible to prove that the parameter is formally related to the heterogeneity Gini index [10, 12]. For a given m, there is one-to-one correspondence among CUB probability distributions and the parameters . ; /. 1 ; 1 / corresponding to uncertainty and satisfaction, respectively, in our study. We can summarize several estimated models as a collection of points in the parameter space and check for possible 40 S.
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In such a way, the analytic derivatives to obtain the asymptotic covariance matrix of the vector of parameter estimates are not needed. Furthermore, since each inference function derives from some log-likelihood of a marginal distribution, the inference can be obtained by the existing EM algorithm implemented for the CUB models. 3 An Empirical Application In order to exemplify the use of the proposed model for a real case study we consider the distribution of ratings that consumers expressed about two types of commercial smoked salmon.