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206
BAYESIAN INFERENCE FOR SURVIVAL DATA WITH NONPARAMETRIC HAZARDS AND VAGUE PRIORS
, 1985
"... Statistical inference is reviewed for survival data applications with hazard models having one parameter per distinct failure time and using Jeffreys ' (1961) vague priors. Distinction between a discrete hazard and a piecewise exponential model is made. Bayes estimators of survival probabilitie ..."
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Cited by 1 (1 self)
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Statistical inference is reviewed for survival data applications with hazard models having one parameter per distinct failure time and using Jeffreys ' (1961) vague priors. Distinction between a discrete hazard and a piecewise exponential model is made. Bayes estimators of survival
use of vague prior distributions in MCMC using WinBUGS
"... How vague is vague? A simulation study of the impact of the ..."
MODEL SELECTION WITH VAGUE PRIOR INFORMATION (AsymptoticslBayes factor/Hypothesis testing/Intrinsic priorslModel comparison)
"... In the Bayesian approach, the Bayes factor is the main too} for mode} selection and hypothesis testing. When prior information is weak, "default " or "automatic " priors, which are typicaIly improper, are commonly used but, unfortunately, the Bayes factor is defined up to a mult ..."
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In the Bayesian approach, the Bayes factor is the main too} for mode} selection and hypothesis testing. When prior information is weak, "default " or "automatic " priors, which are typicaIly improper, are commonly used but, unfortunately, the Bayes factor is defined up to a
Measuring the effect of observations using the posterior and the intrinsic bayes factors with vague prior information
, 1997
"... ..."
Submitted APPROXIMATION OF IMPROPER PRIOR BY VAGUE
"... Abstract. We propose a convergence mode for prior distributions which allows a sequence of probability measures to have an improper limiting measure. We define a sequence of vague priors as a sequence of probability measures that converges to a noninformative prior. We consider some cases where vag ..."
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Abstract. We propose a convergence mode for prior distributions which allows a sequence of probability measures to have an improper limiting measure. We define a sequence of vague priors as a sequence of probability measures that converges to a noninformative prior. We consider some cases where
SHRINKAGE PRIORS FOR BAYESIAN PREDICTION
, 2006
"... We investigate shrinkage priors for constructing Bayesian predictive distributions. It is shown that there exist shrinkage predictive distributions asymptotically dominating Bayesian predictive distributions based on the Jeffreys prior or other vague priors if the model manifold satisfies some diffe ..."
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Cited by 11 (2 self)
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We investigate shrinkage priors for constructing Bayesian predictive distributions. It is shown that there exist shrinkage predictive distributions asymptotically dominating Bayesian predictive distributions based on the Jeffreys prior or other vague priors if the model manifold satisfies some
The Prior Knowledge Effect on the Processing of Vague Discourse in Mandarin Chinese
"... This study investigates whether prior knowledge affects the processing of vague discourse in Mandarin Chinese. Vague discourse refers to the texts using vague references and neutral descriptors (e.g. 東 西 dōngxī "thing", 事 情 shìqíng "item", and 物 件 wùjiàn "object"), ..."
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This study investigates whether prior knowledge affects the processing of vague discourse in Mandarin Chinese. Vague discourse refers to the texts using vague references and neutral descriptors (e.g. 東 西 dōngxī "thing", 事 情 shìqíng "item", and 物 件 wùjiàn "
Semantics and Pragmatics of Vague Probability Expressions
, 1994
"... Two experiments assessed the membership functions that German speakers assign to 12 adverb phrases and 17 modal verb forms that express probability assessments. These expressions fall largely into three rather homogeneous classes. The membership functions are used as part of the semantic knowledge b ..."
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Cited by 6 (3 self)
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base of the natural language dialog system PRACMA, one of whose purposes is to model pragmatic and contextual influenceson the use of vague expressions. The system's normative model accounts for the role, in the selection and interpretation of vague probability expressions, of the listener
A behavioural model for vague probability assessments
, 2003
"... I present an hierarchical uncertainty model that is able to represent vague probability assessments, and to make inferences based on them. This model can be given an interpretation in terms of the behaviour of a modeller in the face of uncertainty, and is based on Walley’s theory of imprecise proba ..."
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Cited by 15 (1 self)
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I present an hierarchical uncertainty model that is able to represent vague probability assessments, and to make inferences based on them. This model can be given an interpretation in terms of the behaviour of a modeller in the face of uncertainty, and is based on Walley’s theory of imprecise
Incorporating Prior Knowledge Regarding the Mean in Bayesian Factor Analysis
 Social Science Working Paper 1097, Division of Humanities and Social Sciences, Caltech, Pasadena, CA 91125
, 2001
"... In the Bayesian factor analysis model (Press & Shigemasu, 1989), available knowledge regarding the model parameters is incorporated in the form of prior distributions. This has the added consequence of eliminating the ambiguity of rotation found in the traditional factor analysis model. In the m ..."
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Cited by 2 (2 self)
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. In the model presented by Press and Shigemasu, a vague prior distribution was implicitly specified for the population mean. The sample size was assumed to be large enough to estimate the overall population mean by the sample mean. In this paper, available prior knowledge regarding the population mean
Results 1  10
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206