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Empirical Evidence Concerning the Finite Sample Performance of EL-Type Structural Equation Estimation and Inference Methods AgEcon
Mittelhammer, Ronald C.; Judge, George G.; Schoenberg, Ron.
This paper presents empirical evidence concerning the finite sample performance of conventional and generalized empirical likelihood-type estimators that utilize instruments in the context of linear structural models characterized by endogenous explanatory variables. There are suggestions in the literature that traditional and non-traditional asymptotically efficient estimators based on moment equations may, for the relatively small sample sizes usually encountered in econometric practice, have relatively large biases and/or variances and provide an inadequate basis for estimation and inference. Given this uncertainty we use a range of data sampling processes and Monte Carlo sampling procedures to accumulate finite sample empirical evidence concerning...
Tipo: Working or Discussion Paper Palavras-chave: Unbiased moment based estimation and inference; Empirical likelihood; Empirical exponential likelihood; Semiparametric models; Conditional estimating equations; Finite sample bias and precision; Squared error loss; Instrumental conditioning variables; Research Methods/ Statistical Methods; C10; C24.
Ano: 2003 URL: http://purl.umn.edu/25090
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An Information-Theoretic Approach to Modeling Binary Choices: Estimating Willingness to Pay for Recreation Site Attributes AgEcon
Henry-Osorio, Miguel; Mittelhammer, Ronald C..
Information-Theoretic Econometrics
Tipo: Presentation Palavras-chave: Minimum power divergence; Cressie-Read statistics; Contingent valuation; Empirical likelihood; Discrete choice; Binary response models; Environmental Economics and Policy; Research Methods/ Statistical Methods; C13; C14; C25; Q51.
Ano: 2012 URL: http://purl.umn.edu/123432
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Maximum likelihood with estimating equations AgEcon
Grendar, Marian; Judge, George G..
Methods, like Maximum Empirical Likelihood (MEL), that operate within the Empirical Estimating Equations (E3) approach to estimation and inference are challenged by the Empty Set Problem (ESP). We propose to return from E3 back to the Estimating Equations, and to use the Maximum Likelihood method. In the discrete case the Maximum Likelihood with Estimating Equations (MLEE) method avoids ESP. In the continuous case, how to make ML-EE operational is an open question. Instead of it, we propose a Patched Empirical Likelihood, and demonstrate that it avoids ESP. The methods enjoy, in general, the same asymptotic properties as MEL.
Tipo: Working or Discussion Paper Palavras-chave: Maximum likelihood; Estimating equations; Empirical likelihood; Research Methods/ Statistical Methods.
Ano: 2010 URL: http://purl.umn.edu/56691
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Revised empirical likelihood AgEcon
Grendar, Marian; Judge, George G..
Empirical Likelihood (EL) and other methods that operate within the Empirical Estimating Equations (E3) approach to estimation and inference are challenged by the Empty Set Problem (ESP). ESP concerns the possibility that a model set, which is data-dependent, may be empty for some data sets. To avoid ESP we return from E3 back to the Estimating Equations, and explore the Bayesian infinite-dimensional Maximum A-posteriori Probability (MAP) method. The Bayesian MAP with Dirichlet prior motivates a Revised EL (ReEL) method. ReEL i) avoids ESP as well as the convex hull restriction, ii) attains the same basic asymptotic properties as EL, and iii) its computation complexity is comparable to that of EL.
Tipo: Working or Discussion Paper Palavras-chave: Empirical estimating equations; Generalized minimum contrast; Empirical likelihood; Generalized empirical likelihood; Empty set problem; Convex hull restriction; Estimating equations; Maximum aposteriori probability; Research Methods/ Statistical Methods.
Ano: 2010 URL: http://purl.umn.edu/91799
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