Estimation and inference with censored and ordered multinomial response data
type: Item
instance of: scholarly article
title: Estimation and inference with censored and ordered multinomial response data
zbMATH Open document ID: 0910.62122
DOI: 10.1016/S0304-4076(97)00006-7
author: Amos Golan
author: George G. Judge
author: Jeffrey M. Perloff
published in: Journal of Econometrics
publication date: 1999-04-22T00:00:00Z
review text: Le modèle de base est le modèle linéaire traditionnel en statistique: \(y^*_t=x_t'\beta+e_t\), où \(x\) est un vecteur observable, \(\beta\) un vecteur de paramètres inconnu et e une perturbation aléatoire. Mais les \(y_t^*\) sont ici supposées non observables. Deux cas sont envisagés: -- l'observation \(y_t\) vaut \(y^*_t\) si \(y_t^*>\mu 1\) et \(\mu 1\) sinon; -- l'observation \(y_t\) prend des valeurs entières étagées selon l'appartenance de \(y^*_t\) à des intervalles de bornes \(\mu 1,\mu 2,\dots\). La méthode d'estimation étudiée est celle de la maximisation de l'entropie (soit \(-\Sigma p_iLn p_i\) pour une distribution de probabilité \(\{p_i\}\)). Après une reformulation matricielle du paramètre et de la perturbation, l'étude des estimateurs est réalisée (variance-covariance, comparaison avec une méthode de moments, propriétés asymptotiques) pour une gamme de distributions de celle-ci (cas non gaussien en particulier). Leur qualité est également examinée sur des données générées (Monte Carlo).
reviewed by: Vidal Cohen
Mathematics Subject Classification ID: 62P20
Mathematics Subject Classification ID: 62J05
zbMATH DE Number: 1042459
zbMATH Keywords: censored data
zbMATH Keywords: maximum entropy estimator
zbMATH Keywords: ordered statistical models
MaRDI profile type: Publication
cites work: An algorithm for finding the distribution of maximal entropy
cites work: Regression Analysis when the Dependent Variable Is Truncated Normal
cites work: The Estimation of a Simultaneous Equation Generalized Probit Model
cites work: Tobit models: A survey
cites work: Q3999497
cites work: Statistical decision theory and Bayesian analysis. 2nd ed
cites work: On a simple estimation procedure for censored regression models with known error distributions
cites work: Linear regression with censored data
cites work: Adjusted Least Squares Estimates for the Scaled Regression Coefficients with Censored Data
cites work: Why least squares and maximum entropy? An axiomatic approach to inference for linear inverse problems
cites work: Q4802629
cites work: Stein's Estimation Rule and Its Competitors--An Empirical Bayes Approach
cites work: Q4368994
cites work: A Maximum Entropy Approach to Recovering Information From Multinomial Response Data
cites work: Q4365235
cites work: Maximum Entropy for Hypothesis Formulation, Especially for Multidimensional Contingency Tables
cites work: On the Asymptotic Bias of the Ordinary Least Squares Estimator of the Tobit Model
cites work: Estimation of limited dependent variable models by ordinary least squares and the method of moments
cites work: Sample Selection Bias as a Specification Error
cites work: Robust Statistics
cites work: Information Theory and Statistical Mechanics
cites work: Q3333811
cites work: An adaptive empirical Bayes estimator of the multivariate normal mean under quadratic loss
cites work: Q3996274
cites work: Q3806648
cites work: Q5750089
cites work: Regression analysis with randomly right-censored data
cites work: Q3260839
cites work: Identification and Estimation in Binary Choice Models with Limited (Censored) Dependent Variables
cites work: An information theoretical approach to inversion problems
cites work: Q3042260
cites work: Least squares regression with censored data
cites work: Robust estimation based on grouped-adjusted data in censored regression models
cites work: A Monte Carlo comparison of estimators for censored regression models
cites work: Least absolute deviations estimation for the censored regression model
cites work: Censored regression quantiles
cites work: Symmetrically Trimmed Least Squares Estimation for Tobit Models
cites work: A Mathematical Theory of Communication
cites work: Axiomatic derivation of the principle of maximum entropy and the principle of minimum cross-entropy
cites work: Estimation of Relationships for Limited Dependent Variables
cites work: A statistical model for the analysis of ordinal level dependent variables
full work available at URL: s0304-4076(97)00006-7
OpenAlex ID: W1989292062
description: scientific article; zbMATH DE number 1042459