Displaying similar documents to “Beliefs about beliefs, a theory for stochastic assessment of subjective probabilities.”

A Bayesian Spatial Mixture Model for FMRI Analysis

Geliazkova, Maya (2010)

Serdica Journal of Computing

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We develop, implement and study a new Bayesian spatial mixture model (BSMM). The proposed BSMM allows for spatial structure in the binary activation indicators through a latent thresholded Gaussian Markov random field. We develop a Gibbs (MCMC) sampler to perform posterior inference on the model parameters, which then allows us to assess the posterior probabilities of activation for each voxel. One purpose of this article is to compare the HJ model and the BSMM in terms of receiver operating characteristics...

Application of MCMC to change point detection

Jaromír Antoch, David Legát (2008)

Applications of Mathematics

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A nonstandard approach to change point estimation is presented in this paper. Three models with random coefficients and Bayesian approach are used for modelling the year average temperatures measured in Prague Klementinum. The posterior distribution of the change point and other parameters are estimated from the random samples generated by the combination of the Metropolis-Hastings algorithm and the Gibbs sampler.

On the number of outliers in data from a linear model.

Peter R. Freeman (1980)

Trabajos de Estadística e Investigación Operativa

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This paper reviews models for the occurrence of outliers in data from the linear model. The Bayesian analyses are all closely similar in form, but differ in the way they treat suspected outliers. The models are compared on Darwin's data and one of them is used on data from a 25 factorial experiment. The question on how many outliers are present involves comparison of models with different number of parameters. A solution using proper priors on all parameters...

Bayesian analysis of structural change in a distributed Lag Model (Koyck Scheme)

Arvin Paul B. Sumobay, Arnulfo P. Supe (2014)

Discussiones Mathematicae Probability and Statistics

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Structural change for the Koyck Distributed Lag Model is analyzed through the Bayesian approach. The posterior distribution of the break point is derived with the use of the normal-gamma prior density and the break point, ν, is estimated by the value that attains the Highest Posterior Probability (HPP). Simulation study is done using R. Given the parameter values ϕ = 0.2 and λ = 0.3, the full detection of the structural change when σ² = 1 is generally attained at...

On the logical development of statistical models.

Daniel Peña (1988)

Trabajos de Estadística

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This paper presents a classification of statistical models using a simple and logical framework. Some remarks are made about the historical appearance of each type of model and the practical problems that motivated them. It is argued that the current stages of the statistical methodology for model building have arisen in response to the needs for more sophisticated procedures for building dynamic-explicative types of models. Some potentially important topics for future research are included. ...

Sampling inference, Bayes' inference and robustness in the advancement of learning.

George E. P. Box (1980)

Trabajos de Estadística e Investigación Operativa

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Scientific learning is seen as an iterative process employing Criticism and Estimation. Sampling theory use of predictive distributions for model criticism is examined and also the implications for significance tests and the theory of precise measurement. Normal theory examples and ridge estimates are considered. Predictive checking functions for transformation, serial correlation, and bad values are reviewed as is their relation with Bayesian options. Robustness is seen from a Bayesian...

Sequential learning, discontinuities and changes: Discussion.

Stephen E. Fienberg, José M. Bernardo, Philip J. Brown, A. Philip Dawid, James M. Dickey, Joseph B. Kadane, Tom Leonard (1980)

Trabajos de Estadística e Investigación Operativa

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Discussion on the papers by Makov, Udi E., Approximation of unsupervised Bayes learning procedures, Smith, Adrian F. M., Change-Point problems: approaches and applications and by Harrison, P. J. and Smith Jim Q., Discontinuity, decision and conflict, the three of them part of a round table on Sequential learning, discontinuities and changes held in the First International Congress on Bayesian Methods (Valencia, Spain, 28 May - 2 June 1979).

An evaluation of the efficiency of plant protection products via nonlinear statistical methods – a simulation study

Ewa Skotarczak, Ewa Bakinowska, Kamila Tomaszyk (2014)

Biometrical Letters

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A nonlinear statistical approach was used to evaluate the efficiency of plant protection products. The methodology presented can be implemented when the observations in an experiment are recorded as success or failure. This occurs, for example, when following the application of a herbicide or pesticide, a single weed or insect is classified as alive (failure) or dead (success). Then a higher probability of success means a higher efficiency of the tested product. Using simulated data...

A Bayesian look at nuisance parameters.

A. Philip Dawid (1980)

Trabajos de Estadística e Investigación Operativa

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The elimination of nuisance parameters has classically been tackled by various ad hoc devices, and has led to a number of attemps to define partial sufficiency and ancillarity. The Bayesian approach is clearly defined. This paper examines some classical procedures in order to see when they can be given a Bayesian justification.