Pages that link to "Item:Q3792070"

The following pages link to Robust Estimation of the Mean and Covariance Matrix from Data with Missing Values (Q3792070):

Displaying 50 items.

• M-estimation with incomplete and dependent multivariate data (Q128879) (← links)
• Expectation-robust algorithm and estimating equations for means and dispersion matrix with missing data (Q263260) (← links)
• Influence diagnostics for robust P-splines using scale mixture of normal distributions (Q287528) (← links)
• Consistency, bias and efficiency of the normal-distribution-based MLE: the role of auxiliary variables (Q392100) (← links)
• A robust extension of the bivariate Birnbaum-Saunders distribution and associated inference (Q392107) (← links)
• High-dimensional covariance matrix estimation with missing observations (Q395991) (← links)
• Stochastic volatility in mean models with heavy-tailed distributions (Q447982) (← links)
• A unified approach to exploratory factor analysis with missing data, nonnormal data, and in the presence of outliers (Q463082) (← links)
• Combining standardized mean differences using the method of maximum likelihood (Q463134) (← links)
• A robust Bayesian approach for structural equation models with missing data (Q477948) (← links)
• Skew scale mixtures of normal distributions: properties and estimation (Q537476) (← links)
• Efficiency of split questionnaire surveys (Q629132) (← links)
• On estimation and local influence analysis for measurement errors models under heavy-tailed distributions (Q641778) (← links)
• Imputation techniques in regression analysis: Looking closely at their implementation (Q672429) (← links)
• Robust structural equation modeling with missing data and auxiliary variables (Q692422) (← links)
• Robust analysis of longitudinal data with nonignorable missing responses (Q715507) (← links)
• Normal distribution based pseudo ML for missing data: with applications to mean and covariance structure analysis (Q842909) (← links)
• A generalization of Tyler's M-estimators to the case of incomplete data (Q962269) (← links)
• Assessment of local influence in elliptical linear models with longitudinal structure (Q1020096) (← links)
• Principal component analysis for data containing outliers and missing elements (Q1023501) (← links)
• EM-type algorithms for computing restricted MLEs in multivariate normal distributions and multivariatet-distributions (Q1023837) (← links)
• Identifying variables responsible for data not missing at random (Q1029514) (← links)
• Wiener processes with random effects for degradation data (Q1049539) (← links)
• ML estimation of the multivariate \(t\) distribution and the EM algorithm (Q1375112) (← links)
• Longitudinal data analysis using \(t\)-type regression. (Q1429889) (← links)
• Likelihood-based inference for multivariate skew scale mixtures of normal distributions (Q1622087) (← links)
• Model-based time-varying clustering of multivariate longitudinal data with covariates and outliers (Q1658183) (← links)
• A Bayesian sensitivity analysis of the effect of different random effects distributions on growth curve models (Q2219419) (← links)
• An estimate of the covariance between variables which are not jointly observed (Q2250651) (← links)
• Maximum likelihood estimation of multinomial probit factor analysis models for multivariate \(t\)-distribution (Q2259075) (← links)
• Maximum likelihood methods in treating outliers and symmetrically heavy-tailed distributions for nonlinear structural equation models with missing data (Q2260979) (← links)
• Mixtures of multivariate contaminated normal regression models (Q2306894) (← links)
• Robust clustering in regression analysis via the contaminated Gaussian cluster-weighted model (Q2403302) (← links)
• Robust Bayesian analysis of heavy-tailed stochastic volatility models using scale mixtures of normal distributions (Q2445744) (← links)
• Parsimonious mixtures of multivariate contaminated normal distributions (Q2833487) (← links)
• Robust joint modeling of longitudinal measurements and time to event data using normal/independent distributions: a Bayesian approach (Q2857992) (← links)
• Gaussian Scale Mixture Models for Robust Linear Multivariate Regression with Missing Data (Q3178490) (← links)
• Joint modelling of location and scale parameters of the t distribution (Q3429986) (← links)
• Robust methods for generalized linear models with nonignorable missing covariates (Q3526431) (← links)
• Missing data in the k-population multivariate normal patterned mean and covariance matrix testing and estimation problem (Q3745072) (← links)
• Robustness of the student t based M-estimator (Q4226921) (← links)
• Choosing among imputation techniques for incomplete multivariate data: a simulation study (Q4275808) (← links)
• A Robust Bayesian Random Effects Model for Nonlinear Calibration Problems (Q4911935) (← links)
• Robust location estimators in regression models with covariates and responses missing at random (Q4988816) (← links)
• A robust multivariate Birnbaum–Saunders regression model (Q4999855) (← links)
• Multiple scaled contaminated normal distribution and its application in clustering (Q5006013) (← links)
• Linear mixed models based on skew scale mixtures of normal distributions (Q5055200) (← links)
• Bayesian analysis of generalized elliptical semi-parametric models (Q5138101) (← links)
• On elliptical multilevel models (Q5138150) (← links)
• A robust multivariate Birnbaum–Saunders distribution: EM estimation (Q5147568) (← links)