Editorial: Recent developments in mixture models (Hamburg, July 2001)
From MaRDI portal
Publication:951793
DOI10.1016/S0167-9473(02)00161-5zbMath1256.62014OpenAlexW2031144387MaRDI QIDQ951793
Seidel, Wilfried, Dankmar Boehning
Publication date: 4 November 2008
Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/s0167-9473(02)00161-5
likelihood ratiounobserved heterogeneitynonparametric maximum likelihoodnumber of componentsapplication studies
Lua error in Module:PublicationMSCList at line 37: attempt to index local 'msc_result' (a nil value).
Related Items (21)
Flexible modelling of survival curves for censored data ⋮ Robust growth mixture models with non-ignorable missingness: models, estimation, selection, and application ⋮ Missing data imputation through GTM as a mixture of \(t\)-distributions ⋮ Bootstrap estimation and model selection for multivariate normal mixtures using parallel computing with graphics processing units ⋮ Computational aspects of fitting mixture models via the expectation-maximization algorithm ⋮ Minimum Hellinger Distance Estimation for k-Component Poisson Mixture with Random Effects ⋮ Moment Estimation for Nonparametric Mixture Models through Implicit Tensor Decomposition ⋮ A geometrical approach to the ordinal data of Likert scaling and attitude measurements: the density matrix in psychology ⋮ New approaches to compute Bayes factor in finite mixture models ⋮ Bayesian analysis of finite mixture models of distributions from exponential families ⋮ Drug risk assessment with determining the number of sub-populations under finite mixture normal models ⋮ Optimization of the number of components in the mixed model using multi-criteria decision-making ⋮ Using conditional independence for parsimonious model-based Gaussian clustering ⋮ Cross‐validation and peeling strategies for survival bump hunting using recursive peeling methods ⋮ Editorial: Advances in mixture models ⋮ Recent asymptotic results in testing for mixtures ⋮ Bayesian analysis of finite mixtures of multinomial and negative-multinomial distributions ⋮ A quick procedure for model selection in the case of mixture of normal densities ⋮ Gaussian mixture model classification: a projection pursuit approach ⋮ Independent factor discriminant analysis ⋮ Estimators for the Finite Mixture of Rayleigh Model Based on Progressively Censored Data
Uses Software
This page was built for publication: Editorial: Recent developments in mixture models (Hamburg, July 2001)