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  • Search: subject:"non-parametric likelihood"
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Year of publication
Subject
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Errors-in-Variables 2 Functional Relations 2 L-divergence 2 Maximum Non-parametric Likelihood 2 Measurement Error 2 Non-parametric Likelihood 2 Orthogonal Regression 2 Partially Linear Model 2 Semiparametric Models 2 Structural Relations 2 Bayesian Large Deviations 1 Bayesian Maximum (A Posteriori) Probability method 1 Bayesian non-parametric consistency 1 Bayesian nonparametric consistency 1 Computerized tomography 1 Empirical Likelihood method 1 Estimating Equations 1 Maximum Non-parametric Likelihood method 1 Polya L-divergence 1 Polya sampling 1 Radon transform 1 Sanov Theorem for Sampling Distributions 1 Social and Behavioral Sciences 1 estimating equations 1 fast Fourier transform 1 non-parametric likelihood 1 positron emission tomography 1 projection-slice theorem 1 random coefficients regression 1 regularization 1 right censoring 1 smoothed EM algorithm 1
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Online availability
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Free 5 Undetermined 1
Type of publication
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Book / Working Paper 5 Article 1
Type of publication (narrower categories)
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Working Paper 1
Language
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Undetermined 5 English 1
Author
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Grendar, Marian 3 Judge, George G. 3 Carroll, Raymond J. 2 Härdle, Wolfgang 2 Liang, Hua 2 Feuerverger, Andrey 1 Niven, R. K. 1 Vardi, Yehuda 1
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Institution
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Department of Agricultural and Resource Economics, University of California-Berkeley 3 Sonderforschungsbereich 373, Quantifikation und Simulation ökonomischer Prozesse, Wirtschaftswissenschaftliche Fakultät 1
Published in...
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Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series 3 Annals of the Institute of Statistical Mathematics 1 SFB 373 Discussion Paper 1 SFB 373 Discussion Papers 1
Source
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RePEc 5 EconStor 1
Showing 1 - 6 of 6
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Consistency of Empirical Likelihood and Maximum A-Posteriori Probability Under Misspecification
Grendar, Marian; Judge, George G. - Department of Agricultural and Resource Economics, … - 2008
Using a large deviations approach, Maximum A-Posteriori Probability (MAP) and Empirical Likelihood (EL) are shown to possess, under misspecification, an exclusive property of Bayesian consistency. Under conditions of consistency, regardless of prior the MAP estimator asymptotically coincides...
Persistent link: https://www.econbiz.de/10010537314
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Large Deviations Approach to Bayesian Nonparametric Consistency: the Case of Polya Urn Sampling
Grendar, Marian; Judge, George G.; Niven, R. K. - Department of Agricultural and Resource Economics, … - 2007
, Bayesian nonparametric consistency is established. Polya BST is also used to provide an extension of Maximum Non-parametric … Likelihood and Empirical Likelihood methods to the Polya case. …
Persistent link: https://www.econbiz.de/10010537510
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A Bayesian Large Deviations Probabilistic Interpretation and Justification of Empirical Likelihood
Grendar, Marian; Judge, George G. - Department of Agricultural and Resource Economics, … - 2007
In this paper we demonstrate, in a parametric Estimating Equations setting, that the Empirical Likelihood (EL) method is an asymptotic instance of the Bayesian non-parametric Maximum-A-Posteriori approach. The resulting probabilistic interpretation and justifcation of EL rests on Bayesian...
Persistent link: https://www.econbiz.de/10010676623
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Large sample theory in a semiparametric partially linear errors-in-variables models
Liang, Hua; Härdle, Wolfgang; Carroll, Raymond J. - 1997
We consider the partially linear model relating a response Y to predictors (X,T) with mean function XT ß + g (T) when the X's are measured with additive error. The semiparametric likelihood estimate of Severini and Staniswalis (1994) leads to biased estimates of both the parameter ß and the...
Persistent link: https://www.econbiz.de/10010310770
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Large sample theory in a semiparametric partially linear errors-in-variables models
Liang, Hua; Härdle, Wolfgang; Carroll, Raymond J. - Sonderforschungsbereich 373, Quantifikation und … - 1997
We consider the partially linear model relating a response Y to predictors (X,T) with mean function XT ß + g (T) when the X's are measured with additive error. The semiparametric likelihood estimate of Severini and Staniswalis (1994) leads to biased estimates of both the parameter ß and the...
Persistent link: https://www.econbiz.de/10010983828
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Positron Emission Tomography and Random Coefficients Regression
Feuerverger, Andrey; Vardi, Yehuda - In: Annals of the Institute of Statistical Mathematics 52 (2000) 1, pp. 123-138
Persistent link: https://www.econbiz.de/10005616189
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