Treffer: An ECM Estimation Approach for Analyzing Multivariate Skew-Normal Data with Dropout
Title:
An ECM Estimation Approach for Analyzing Multivariate Skew-Normal Data with Dropout
Authors:
Source:
Communications in statistics. Simulation and computation. 41(8-10):1970-1988
Publisher Information:
Colchester: Taylor & Francis, 2012.
Publication Year:
2012
Physical Description:
print, 1 p.1/2
Original Material:
INIST-CNRS
Subject Terms:
Mathematics, Mathématiques, Sciences exactes et technologie, Exact sciences and technology, Sciences et techniques communes, Sciences and techniques of general use, Mathematiques, Mathematics, Probabilités et statistiques, Probability and statistics, Statistiques, Statistics, Lois de probabilités, Distribution theory, Analyse multivariable, Multivariate analysis, Inférence linéaire, régression, Linear inference, regression, Analyse numérique. Calcul scientifique, Numerical analysis. Scientific computation, Analyse numérique, Numerical analysis, Probabilités et statistiques numériques, Numerical methods in probability and statistics, Algorithme EM, EM algorithm, Algoritmo EM, Analyse multivariable, Multivariate analysis, Análisis multivariable, Comportement asymptotique, Asymptotic behavior, Comportamiento asintótico, Distribution statistique, Statistical distribution, Distribución estadística, Estimation erreur, Error estimation, Estimación error, Estimation non paramétrique, Non parametric estimation, Estimación no paramétrica, Estimation statistique, Statistical estimation, Estimación estadística, Loi n variables, Multivariate distribution, Ley n variables, Loi normale, Gaussian distribution, Curva Gauss, Maximum vraisemblance, Maximum likelihood, Maxima verosimilitud, Mesure information, Information measure, Medida información, Méthode statistique, Statistical method, Método estadístico, Performance algorithme, Algorithm performance, Resultado algoritmo, Régression statistique, Statistical regression, Regresión estadística, Simulation numérique, Numerical simulation, Simulación numérica, Simulation statistique, Statistical simulation, Simulación estadística, Test hypothèse, Hypothesis test, Test hipótesis, Test statistique, Statistical test, Test estadístico, Théorie approximation, Approximation theory, Théorie information, Information theory, Teoría información, Théorie statistique, Statistical theory, Teoría estadística, 62B10, 62E17, 62F03, 62F12, 62G20, 62H10, 62H12, 62Jxx, Donnée longitudinale, Estimation paramétrique, Matrice information, Information matrix, Mesure asymétrie, Skewness measure, 62P10, Dropout, ECM algorithm, Longitudinal data, Skew-normal distribution
Document Type:
Fachzeitschrift
Article
File Description:
text
Language:
English
Author Affiliations:
Department of Statistics, Shahid Beheshti University, Tehran, Iran, Islamic Republic of
ISSN:
0361-0918
Rights:
Copyright 2015 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Mathematics
Accession Number:
edscal.26164038
Database:
PASCAL Archive
Weitere Informationen
In this article, an ECM algorithm is developed to obtain the maximum likelihood estimates of parameters where multivariate skew-normal distribution is used for analyzing longitudinal skewed normal regression data with dropout. A simulation study is performed to investigate the performance of the presented algorithm. Also, the methodology is illustrated through two applications and the results of proposed methodology are compared with ECM under multivariate normal assumption using AIC and BIC criteria. Standard errors of parameter estimates are obtained by asymptotic observed information matrix.