… This chapter reviews the literature related to finite mixture models designed specifically for
… aim of this section is to describe some models for multivariate count data, explain how finite …

… on statistical modeling in presence of a possible endogenous binary … multivariate distribution
for the random terms, we obtain a multivariate mixed-responses finite mixture model, in …

… endogenous switching mixture models deal mainly with continuous or binary outcomes.
Models with ordinal or count … In mixture models, the likelihood function may have multiple local …

… It suggests that the unobserved error terms follow a mixture distribution of multiple normal …
In this section, we estimate a normal mixture model using simulated data and examine …

… In the second stage, the estimator of gregariousness is included in the count data model as
a supplementary explanatory variable.I find that the network is endogenous and that ignoring …

… of copula-based finite mixture models for clustering applications. … The closure properties
of the mixture models under … construction of multivariate mixture models for continuous …

… handle binary endogenous regressors and count endogenous … SORE models the multivariate
distribution of endogenous … samples collected via endogenous selective sampling, which …

… Intrinsic timescales characterize dynamics of endogenous fluctuations … Our results suggest
that multiple timescales may arise from … The shape of spike-count autocorrelations in our data …

… In addition to these endogenous changes in E:I balance, … constant multisensory input, selective
attention entails a … To this end, we inverted linear mixed models to either include auditory …

… The mean vector \(\varvec{\mu }_{it}\) is modelled in a regression framework by defining a
multivariate linear mixed model as a function of a set of p covariates \(\mathbf{x}_{it} = (1,x_{it1},…