Pages that link to "Item:Q4386045"

The following pages link to Testing in locally conic models, and application to mixture models (Q4386045):

Displaying 38 items.

• Robust estimation for the order of finite mixture models (Q451302) (← links)
• Asymptotics for regression models under loss of identifiability (Q505478) (← links)
• Density estimation by the penalized combinatorial method (Q558002) (← links)
• Asymptotic distribution and local power of the likelihood ratio test for mixtures: bounded and unbounded cases (Q882879) (← links)
• A modified likelihood ratio test for homogeneity in bivariate normal mixtures of two samples (Q967994) (← links)
• Recent asymptotic results in testing for mixtures (Q1020205) (← links)
• Asymptotics for likelihood ratio tests under loss of identifiability (Q1412366) (← links)
• Likelihood ratio of unidentifiable models and multilayer neural networks (Q1412367) (← links)
• Singularities in mixture models and upper bounds of stochastic complexity. (Q1422259) (← links)
• Testing the order of a model using locally conic parametrization: Population mixtures and stationary ARMA processes (Q1568265) (← links)
• Unsupervised learning of mixture regression models for longitudinal data (Q1662922) (← links)
• Asymptotic theory of the likelihood ratio test for the identification of a mixture (Q1772674) (← links)
• Asymptotic analysis of Bayesian generalization error with Newton diagram (Q1784534) (← links)
• Concentration inequalities, large and moderate deviations for self-normalized empirical processes (Q1872304) (← links)
• Likelihood ratio tests based on subglobal optimization: A power comparison in exponential mixture models (Q1961770) (← links)
• Likelihood ratio tests of the number of components in a normal mixture with unequal variances (Q2483837) (← links)
• Theoretical analysis of power in a two-component normal mixture model (Q2485978) (← links)
• Asymptotic Poisson character of extremes in non-stationary Gaussian models (Q2488433) (← links)
• The likelihood ratio test for homogeneity in bivariate normal mixtures (Q2489764) (← links)
• Algebraic analysis for nonidentifiable learning machines (Q2731456) (← links)
• (Q3099430) (← links)
• On the Problem in Model Selection of Neural Network Regression in Overrealizable Scenario (Q3149529) (← links)
• Variational Bayes Solution of Linear Neural Networks and Its Generalization Performance (Q3440433) (← links)
• Robust estimation for order of hidden Markov models based on density power divergences (Q3589953) (← links)
• Bounds and asymptotic expansions for the distribution of the Maximum of a smooth stationary Gaussian process (Q4265262) (← links)
• The likelihood ratio test for the number of components in a mixture with Markov regime (Q4504586) (← links)
• On Recursive Estimation in Incomplete Data Models (Q4949637) (← links)
• Singularity Structures and Impacts on Parameter Estimation in Finite Mixtures of Distributions (Q5025768) (← links)
• Universal inference (Q5073098) (← links)
• Penalized proportion estimation for non parametric mixture of regressions (Q5077371) (← links)
• A new model selection procedure for finite mixture regression models (Q5077504) (← links)
• Parameter Identifiability in Statistical Machine Learning: A Review (Q5380697) (← links)
• A statistical test for mixture detection with application to component identification in multidimensional biomolecular NMR studies (Q5413638) (← links)
• Dynamics of Learning Near Singularities in Layered Networks (Q5453542) (← links)
• Difficulty of Singularity in Population Coding (Q5706664) (← links)
• The likelihood ratio test for general mixture models with or without structural parameter (Q5851024) (← links)
• Determining the number of components in mixtures of linear models. (Q5958421) (← links)
• Likelihood asymptotics in nonregular settings: a review with emphasis on the likelihood ratio (Q6577816) (← links)