[PDF] Top 20 Some Remarks on Consistency and Strong Inconsistency of Bayesian Inference
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Some Remarks on Consistency and Strong Inconsistency of Bayesian Inference
... to strong inconsistency and incoherence. Our contribution is, to some extent, a partial re–validation of the Jeffreys’ ...coherent Bayesian inference. By our criterion, the coherence of ... See full document
20
Consistency of Bayesian nonparametric inference for discretely observed jump diffusions
... irreducible strong Feller processes are equivalent to the associated transition probabilities, which is sufficient in this ...the strong Feller property by Theorem ... See full document
24
Bayesian non parametric inference for Λ coalescents : posterior consistency and a parametric method
... The consistency con- ditions of Theorem 2 on the prior are sufficiently mild to permit the use of Dirichlet pro- cess mixture model priors, which can be readily truncated for implementable ...the inference ... See full document
33
Confounding and missing data in cost-effectiveness analysis: comparing different methods
... confounding. Some statis- tical methods have been developed to estimate adjusted means using (generalized) linear models, but it seems that these methods have seldom been applied in cost- effectiveness ...In ... See full document
11
Bayesian InferenceA pproach to Inverse P roblems in aFi nancial MathematicalM odel
... a Bayesian inference ...the Bayesian inference ...the Bayesian inference approach can simultaneously estimate the unknown drift and volatility coefficients from the measured ... See full document
14
Modelling the dynamics of angles of human RR intervals
... a satisfactory description of the observed dynamics as control parameters were changed. All the models mentioned above attempted to capture the behavior of the R–R intervals themselves, without expanding them into any ... See full document
21
Inferences for Burr-X Model Based on Unified Hybrid Censored Data
... where, U is a random number generated from U(0,1). The M LEs of the unknown parameter α and the reliability function R(t) are obtained from (6) and (7), respectively. By using Metropolis-Hastings sampler, we generate a ... See full document
7
A bounded consistency theorem for strong summabilities
... In the main Theorem of [3] Freedman actually proved a consistency theorem for the strong convergence fields of generalized limits.. This statement will be explained at the end of Section[r] ... See full document
8
Strong Memory Consistency For Parallel Programming
... memory consistency models rule out some possible failures, but are limited by depending on subtle programmer-defined locking code and by providing unintuitive semantics for incorrectly synchronized ... See full document
128
Strong Consistency of CVaR Optimal Estimator
... Because of inherent market instability, the ability to assess risk is very important so as to hedge against catastrophic loss. Therefore, some scholars have put for- ward the theory of value at risk (VaR) and ... See full document
11
Similarity-based methods for potential human microRNA-disease association prediction
... experimentally verified miRNA-disease associations to the total experimentally verified miRNA-disease associations. Specificity refers to the percentage of associations that are below the threshold. A receiver-operating ... See full document
9
Approximate Kernel Selection with Strong Approximate Consistency
... first strong approximate consistency of the Nystr¨om approx- imate kernel selection ...approximate consistency of the proposed adaptive Nystr¨om approximate kernel selection method as compared to the ... See full document
8
SOME REMARKS ON THE MULTIVERS CONCEPT
... “As multiverse theories gain credence, the sticky issue of how to compute probabilities in physics is growing from a minor nuisance into a major embarrassment” [8]. This Tegmark’s remark is even truer than one could ... See full document
10
Strong Consistency of Estimators under Missing Responses
... To deal with missing data, one method is to impute a plausible value for each missing datum and then analyze the results as if they are complete. In regression problems, common imputation approaches include linear ... See full document
11
Note on Posterior Inference for the Bingham Distribution
... propose Bayesian inference for the Bingham distribution and they use developments in Bayesian computation for dis- tributions with doubly intractable normalising constants (Møller et ... See full document
10
Remarks on some starlike functions
... MSC: Primary 30C45; secondary 30C80 Keywords: differential subordinations; Nunokawa’s lemma; starlike functions of order alpha; convex functions of order alpha; strongly starlike function[r] ... See full document
8
Some remarks on Cîrtoaje’s conjecture
... The study of inequalities with power-exponential functions is one of the active areas of research in the mathematical analysis. The power-exponential functions have useful ap- plications in mathematical analysis and in ... See full document
11
PAIRWISE JUDGMENTS CONSISTENCY IMPACT ON QUALITY OF MULTI-CRITERIA GROUP DECISION-MAKING WITH AHP
... It is emphasized that thus far only few papers have dealt with the problem concerning the relation between the level of the pairwise judgments (in)consistency and the size of possible estimation errors for ... See full document
18
Bayesian Inference on Gravitational Waves
... the Bayesian MCMC approach for the detection and parameter estimation of signals that can be modeled using some mathematical formalism is quite simple and easy to ... See full document
21
Coverage probability bias, objective Bayes and the likelihood principle
... also some prospect of computer implementa- tion of predictive matching priors via local solutions to equation ...In some cases it may be possible to incorporate local predictive matching priors within Gibbs ... See full document
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