[PDF] Top 20 Exact Bayesian inference for the Bingham distribution
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Exact Bayesian inference for the Bingham distribution
... As an illustration of an application to real data, we con- sider an analysis of earthquake data recently analysed by Arnold and Jupp (2013). An earthquake gives rise to three orthogonal axes, and geophysicists are inter- ... See full document
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Exact and efficient Bayesian inference for multiple changepoint problems
... Much recent research for changepoint models is based on the use of MCMC. For models with an unknown number of changepoints, a common approach is that of Green (1995). A set of models, each incorporating a different ... See full document
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Approximate Bayesian computation (ABC) gives exact results under the assumption of model error
... give exact inference without any assumption of model ...then exact inference using the rejection algorithm would not be possible, and so this approach has the potential to give a significant ... See full document
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Bayesian Inference and Prediction of Burr Type XII Distribution for Progressive First Failure Censored Sampling
... (MLEs), exact confidence intervals and exact confidence regions for the parameters of the Gompertz and Burr type XII distributions based on first-failure-censored sampling, ... See full document
11
Adding Constraints to Bayesian Inverse Problems
... a Bayesian inference ...posterior distribution of the parameters conditioned on (1) the observed data and (2) satisfaction of the constraints is obtained, and the estimate of the parame- ters is ... See full document
8
Bayesian bin distribution inference and mutual information
... This answer can be given by Bayesian inference. In fact, when one is willing to accept some very natural consistency require- ments, it provides the only valid answer, as demonstrated by [5]. The difficulty ... See full document
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Bayesian Inference For The Segmented Weibull Distribution
... classical inference approach, Matthews, Farewell & Pyke (1985) considered an asymptotic score statistic process to test for constant hazard against a change-point ...the exact null and alternative ... See full document
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Adaptive Bayesian inference on the mean of an infinite-dimensional normal distribution
... A bound for the entropy of Sobolev balls was obtained in Theorem 5.2 of Birman and Solomjak (1967). It may be possible to derive a bound similar to that in Lemma 6.4 from their result by a Fourier transformation. ... See full document
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Exact Bayesian inference for animal movement in continuous time
... An important feature of some recent models (Johnson et al. 2008; Fleming et al. 2014a,b) is the autocorrelation of veloci- ties over time, not represented within the ‘building blocks’ described here or in Harris & ... See full document
13
Note on Posterior Inference for the Bingham Distribution
... high-dimensional Bingham distributions have been studied by Kume and Walker ...propose Bayesian inference for the Bingham distribution and they use developments in Bayesian ... See full document
10
Investigations in Exact Inference for Hierarchical Translation
... The approach we have presented is, to our knowl- edge, the first one to address the problem of ex- act sampling for hierarchical translation and to do that in a framework that also handles exact opti- misation. ... See full document
12
Performance of Bayesian Latent Factor Models in Measuring Pricing Errors
... Our study contributes to a body of research focusing on different aspects of the asset pricing, financial econometrics and Bayesian modelling literature. The motivation and aim of this paper is closely related to ... See full document
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Research of Data Model under Exponential Distribution Based on Type I Hybrid Censored Sample
... In this section, we propose different confidence intervals of the scale parameter when B 1 . Using the stochastic monotonicity, we can construct the exact confidence interval for ˆ , we also present the ... See full document
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SIDER : an R package for predicting trophic discrimination factors of consumers based on their ecology and phylogenetic relatedness
... Stable isotope mixing models (SIMMs) are an important tool used to study species’ trophic ecology. These models are dependent on, and sensitive to, the choice of trophic discrimination factors (TDF) representing the ... See full document
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Adaptive Exact Inference in Graphical Models
... HMMs are a widely-used tool to analyze DNA and amino acid sequences; typically an HMM is trained using a sequence with known function or annotations, and new sequences are analyzed by inferring hidden states in the ... See full document
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PCFGs, Topic Models, Adaptor Grammars and Learning Topical Collocations and the Structure of Proper Names
... Over the last few years there has been consider- able interest in Bayesian inference for complex hi- erarchical models both in machine learning and in computational linguistics. This paper establishes a ... See full document
10
A Bayesian Quantile Regression Analysis of Potential Risk Factors for Violent Crimes in USA
... further, this method could also be among the comparison choices. Another limitation is that not many risk factors are considered in this project, but this can be easily ex- tended in Bayesian quantile regression ... See full document
8
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
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
Flexible linear mixed models with improper priors for longitudinal and survival data
... posterior distribution that also allow for censored observa- tions, covering virtually all models in the recent ...posterior distribution of linear regression models with random effects, which requires ... See full document
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