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  • Search: subject:"Non parametric Bayesian Statistics"
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Year of publication
Subject
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concentration parameter 2 discrete baseline 2 empirical study 2 grid method 2 non-parametric Bayesian statistics 2 Bayes-Statistik 1 Bayesian inference 1 Binary response models 1 Dirichlet processes 1 Estimation theory 1 Identification 1 Nichtparametrisches Verfahren 1 Non parametric Bayesian Statistics 1 Nonparametric statistics 1 Sampling 1 Schätztheorie 1 Statistical theory 1 Statistische Methodenlehre 1 Stichprobenerhebung 1
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Online availability
All
Free 3 CC license 1
Type of publication
All
Article 2 Book / Working Paper 1
Type of publication (narrower categories)
All
Article 1 Article in journal 1 Aufsatz in Zeitschrift 1
Language
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English 2 Undetermined 1
Author
All
Liu, Yang 2 Nandram, Balgobin 2 MOUCHART, Michel 1 ROLIN, Jean-Marie 1 SCHEIHING, Eliana 1
Institution
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Center for Operations Research and Econometrics (CORE), École des Sciences Économiques de Louvain 1
Published in...
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CORE Discussion Papers 1 Statistics in Transition new series (SiTns) 1 Statistics in transition : an international journal of the Polish Statistical Association and Statistics Poland 1
Source
All
ECONIS (ZBW) 1 EconStor 1 RePEc 1
Showing 1 - 3 of 3
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Sampling methods for the concentration parameter and discrete baseline of the Dirichlet Process
Liu, Yang; Nandram, Balgobin - In: Statistics in transition : an international journal of … 23 (2022) 4, pp. 21-36
There are many models in the current statistical literature for making inferences based on samples selected from a finite population. Parametric models may be problematic because statistical inference is sensitive to parametric assumptions. The Dirichlet process (DP) prior is very flexible and...
Persistent link: https://www.econbiz.de/10014287820
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Cover Image
Sampling methods for the concentration parameter and discrete baseline of the Dirichlet Process
Liu, Yang; Nandram, Balgobin - In: Statistics in Transition new series (SiTns) 23 (2022) 4, pp. 21-36
There are many models in the current statistical literature for making inferences based on samples selected from a finite population. Parametric models may be problematic because statistical inference is sensitive to parametric assumptions. The Dirichlet process (DP) prior is very flexible and...
Persistent link: https://www.econbiz.de/10015051615
Saved in:
Cover Image
Bayesian identification of semi-parametric binary response models
MOUCHART, Michel; ROLIN, Jean-Marie; SCHEIHING, Eliana - Center for Operations Research and Econometrics (CORE), … - 1998
In this paper, minimal conditions under which a semi-parametric binary response model is identified in a Bayesian framework are presented and compared to the conditions usually required in a sampling theory framework.
Persistent link: https://www.econbiz.de/10005043191
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