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Full-Text Articles in Physical Sciences and Mathematics
Jmasm 51: Bayesian Reliability Analysis Of Binomial Model – Application To Success/Failure Data, M. Tanwir Akhtar, Athar Ali Khan
Jmasm 51: Bayesian Reliability Analysis Of Binomial Model – Application To Success/Failure Data, M. Tanwir Akhtar, Athar Ali Khan
Journal of Modern Applied Statistical Methods
Reliability data are generated in the form of success/failure. An attempt was made to model such type of data using binomial distribution in the Bayesian paradigm. For fitting the Bayesian model both analytic and simulation techniques are used. Laplace approximation was implemented for approximating posterior densities of the model parameters. Parallel simulation tools were implemented with an extensive use of R and JAGS. R and JAGS code are developed and provided. Real data sets are used for the purpose of illustration.
Of Typicality And Predictive Distributions In Discriminant Function Analysis, Lyle W. Konigsberg, Susan R. Frankenberg
Of Typicality And Predictive Distributions In Discriminant Function Analysis, Lyle W. Konigsberg, Susan R. Frankenberg
Human Biology Open Access Pre-Prints
While discriminant function analysis is an inherently Bayesian method, researchers attempting to estimate ancestry in human skeletal samples often follow discriminant function analysis with the calculation of frequentist-based typicalities for assigning group membership. Such an approach is problematic in that it fails to account for admixture and for variation in why individuals may be classified as outliers, or non-members of particular groups. This paper presents an argument and methodology for employing a fully Bayesian approach in discriminant function analysis applied to cases of ancestry estimation. The approach requires adding the calculation, or estimation, of predictive distributions as the final step …
Bayesian Analysis Of Location-Scale Family Of Distributions Using S-Plus And R Software, Sheikh Parvaiz Ahmad, Aquil Ahmed, Athar Ali Khan
Bayesian Analysis Of Location-Scale Family Of Distributions Using S-Plus And R Software, Sheikh Parvaiz Ahmad, Aquil Ahmed, Athar Ali Khan
Journal of Modern Applied Statistical Methods
The Normal and Laplace’s methods of approximation for posterior density based on the location-scale family of distributions in terms of the numerical and graphical simulation are examined using S-PLUS and R Software.
Bayesian Analysis Of Evidence From Studies Of Warfarin V Aspirin For Symptomatic Intracranial Stenosis, Vicki Hertzberg, Barney Stern, Karen Johnston
Bayesian Analysis Of Evidence From Studies Of Warfarin V Aspirin For Symptomatic Intracranial Stenosis, Vicki Hertzberg, Barney Stern, Karen Johnston
Journal of Modern Applied Statistical Methods
Bayesian analyses of symptomatic intracranial stenosis studies were conducted to compare the benefits of long-term therapy with warfarin to aspirin. The synthesis of evidence of effect from previous nonrandomized studies in monitoring a randomized clinical trial was of particular interest. Sequential Bayesian learning analysis was conducted and Bayesian hierarchical random effects models were used to incorporate variability between studies. The posterior point estimates for the risk rate ratio (RRR) were similar between analyses, although the interval estimates resulting from the hierarchical analyses are larger than the corresponding Bayesian learning analyses. This demonstrated the difference between these methods in accounting for …
Bayesian Analysis Of Poverty Rates: The Case Of Vietnamese Provinces, Dominique Haughton, Nguyen Phong
Bayesian Analysis Of Poverty Rates: The Case Of Vietnamese Provinces, Dominique Haughton, Nguyen Phong
Journal of Modern Applied Statistical Methods
This paper presents a Bayesian analysis of poverty rates in urban Ho Chi Minh City and rural Nghe An province in Vietnam. Using mixtures of beta distributions as priors for the poverty rates, we find that, when the prior is reasonably informative, our approach yields more accurate estimated poverty rates than a frequentist approach. On the other hand, we find that, in the presence of poor/non-poor misclassification, average probabilities of posterior credible intervals for poverty rates can fall well short of .95 even with sample sizes such as 2000 or 3000 when the width of the interval is for example …