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Year of publication
Subject
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Bayesian inference 1 Gibbs sampling 1 M test 1 Multinomial process 1 Proportion shifts 1 asymptotic and finite sample risk 1 data dependent shrinkage 1 empirical likelihood procedures 1 endogeneity 1 misclassified data 1 multinomial process 1 noisy multinomial process 1 quadratic loss 1 semiparametric estimation and inference 1
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Online availability
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Undetermined 2 Free 1
Type of publication
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Article 2 Book / Working Paper 1
Language
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Undetermined 3
Author
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Giron, F. J. 1 Hou, Chia-Ding 1 Huang, Sheng 1 Judge, George G. 1 Martin, J. 1 Mittelhammer, Ron C 1 Perez, C. J. 1 Rojano, C. 1 Ruiz, M. 1
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Institution
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Department of Agricultural and Resource Economics, University of California-Berkeley 1
Published in...
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Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series 1 Journal of Applied Statistics 1 Statistics & Probability Letters 1
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RePEc 3
Showing 1 - 3 of 3
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Identifying the source of proportion shifts in a multinomial process using a simple statistical test procedure
Hou, Chia-Ding; Huang, Sheng - In: Statistics & Probability Letters 83 (2013) 4, pp. 1100-1105
process shifts for a multinomial process. A simple detection procedure that utilizes the M test method is proposed for … identifying the source of process variation for a multinomial process. An illustrative example is provided to show how to apply … identify the source of proportion shifts for a multinomial process. …
Persistent link: https://www.econbiz.de/10010662306
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Estimating the Link Function in Multinomial Response Models under Endogeneity and Quadratic Loss
Judge, George G.; Mittelhammer, Ron C - Department of Agricultural and Resource Economics, … - 2004
This paper considers estimation and inference for the multinomial response model in the case where endogenous variables are arguments of the unknown link function. Semiparametric estimators are proposed that avoid the parametric assumptions underlying the likelihood approach as well as the loss...
Persistent link: https://www.econbiz.de/10010537491
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A Bayesian model for multinomial sampling with misclassified data
Ruiz, M.; Giron, F. J.; Perez, C. J.; Martin, J.; Rojano, C. - In: Journal of Applied Statistics 35 (2008) 4, pp. 369-382
In this paper the issue of making inferences with misclassified data from a noisy multinomial process is addressed. A …
Persistent link: https://www.econbiz.de/10005458310
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