Search results for "Bayesian probability"
showing 10 items of 217 documents
Geographical variation in pharmacological prescription
2009
Promoting rational drug administration in treatments is one of the most important issues in Public Health. Bayesian hierarchical models are a very useful tool for incorporating geographical information into the analysis of pharmacological prescription data. They allow the mapping of spatial components which express the trend of geographical variation. In addition, these models are able to deal with uncertainty in a sequential way through prior distributions on parameters and hyperparameters. Bayes' theorem combines all types of information and provides the posterior distribution which is computed through Markov Chain Monte Carlo (MCMC) simulation methods. Simulated data for pharmacological …
A Naïve Sticky Information Model of Households’ Inflation Expectations
2009
This paper provides a simple epidemiology model where households, when forming their inflation expectations, rationally adopt the past release of inflation with certain probability rather than the forward-looking newspaper forecast as suggested in Carroll [2003, Macroeconomic Expectations of Households and Professional Forecasters, Quarterly Journal of Economics, 118, 269-298]. The posterior model probabilities based on the Michigan survey data strongly support the proposed model. We also extend the agent-based epidemiology model by deriving for it a simple adaptation, which is suitable for estimation. Our results show that this model is able to capture the heterogeneity in households’ expe…
Inflation shocks and income inequality
2019
Purpose The purpose of this paper is to analyze the effects of inflationary shocks on inequality, using data of selected countries of the Middle East and North Africa (MENA). Design/methodology/approach Inflationary shocks were measured as deviations from core inflation, based on a genetic algorithm. Bayesian quantile regression was used to estimate the impact of inflationary shocks in different levels of inequality. Findings The results showed that inflationary shocks substantially affect countries with higher levels of inequality, thus suggesting that the detrimental impact of inflation is exacerbated by the high division of classes in a country. Originality/value The study contributes t…
Generalized Bayesian Pursuit: A Novel Scheme for Multi-Armed Bernoulli Bandit Problems
2011
In the last decades, a myriad of approaches to the multi-armed bandit problem have appeared in several different fields. The current top performing algorithms from the field of Learning Automata reside in the Pursuit family, while UCB-Tuned and the e-greedy class of algorithms can be seen as state-of-the-art regret minimizing algorithms. Recently, however, the Bayesian Learning Automaton (BLA) outperformed all of these, and other schemes, in a wide range of experiments. Although seemingly incompatible, in this paper we integrate the foundational learning principles motivating the design of the BLA, with the principles of the so-called Generalized Pursuit algorithm (GPST), leading to the Gen…
The fundamental theory of optimal "Anti-Bayesian" parametric pattern classification using order statistics criteria
2013
Author's version of an article in the journal: Pattern Recognition. Also available from the publisher at: http://dx.doi.org/10.1016/j.patcog.2012.07.004 The gold standard for a classifier is the condition of optimality attained by the Bayesian classifier. Within a Bayesian paradigm, if we are allowed to compare the testing sample with only a single point in the feature space from each class, the optimal Bayesian strategy would be to achieve this based on the (Mahalanobis) distance from the corresponding means. The reader should observe that, in this context, the mean, in one sense, is the most central point in the respective distribution. In this paper, we shall show that we can obtain opti…
Bayesian modeling of the evolution of male height in 18th century Finland from incomplete data.
2012
Abstract Data on army recruits’ height are frequently available and can be used to analyze the economics and welfare of the population in different periods of history. However, such data are not a random sample from the whole population at the time of interest, but instead is skewed since the short men were less likely to be recruited. In statistical terms this means that the data are left-truncated. Although truncation is well-understood in statistics a further complication is that the truncation threshold is not known, may vary from time to time, and auxiliary information on the threshold is not at our disposal. The advantage of the fully Bayesian approach presented here is that both the …
Cancer mortality inequalities in urban areas: a Bayesian small area analysis in Spanish cities
2011
incluye "Erratum to: Cancer mortality inequalities in urban areas: a Bayesian small area analysis in Spanish cities" BACKGROUND: Intra-urban inequalities in mortality have been infrequently analysed in European contexts. The aim of the present study was to analyse patterns of cancer mortality and their relationship with socioeconomic deprivation in small areas in 11 Spanish cities. METHODS: It is a cross-sectional ecological design using mortality data (years 1996-2003). Units of analysis were the census tracts. A deprivation index was calculated for each census tract. In order to control the variability in estimating the risk of dying we used Bayesian models. We present the RR of the censu…
Can bayesian models play a role in dental caries epidemiology? Evidence from an application to the BELCAP data set
2012
Objectives The aim of this study was to show the potential of Bayesian analysis in statistical modelling of dental caries data. Because of the bounded nature of the dmft (DMFT) index, zero-inflated binomial (ZIB) and beta-binomial (ZIBB) models were considered. The effects of incorporating prior information available about the parameters of models were also shown. Methods The data set used in this study was the Belo Horizonte Caries Prevention (BELCAP) study (Bohning et al. (1999)), consisting of five variables collected among 797 Brazilian school children designed to evaluate four programmes for reducing caries. Only the eight primary molar teeth were considered in the data set. A data aug…
Bayesian forecasting with the Holt–Winters model
2010
Exponential smoothing methods are widely used as forecasting techniques in inventory systems and business planning, where reliable prediction intervals are also required for a large number of series. This paper describes a Bayesian forecasting approach based on the Holt–Winters model, which allows obtaining accurate prediction intervals. We show how to build them incorporating the uncertainty due to the smoothing unknowns using a linear heteroscedastic model. That linear formulation simplifies obtaining the posterior distribution on the unknowns; a random sample from such posterior, which is not analytical, is provided using an acceptance sampling procedure and a Monte Carlo approach gives …
Bayesian methods in cost-effectiveness studies: objectivity, computation and other relevant aspects.
2009
In a probabilistic sensitivity analysis (PSA) of a cost-effectiveness (CE) study, the unknown parameters are considered as random variables. A crucial question is what probabilistic distribution is suitable for synthesizing the available information (mainly data from clinical trials) about these parameters. In this context, the important role of Bayesian methodology has been recognized, where the parameters are of a random nature. We explore, in the context of CE analyses, how formal objective Bayesian methods can be implemented. We fully illustrate the methodology using two CE problems that frequently appear in the CE literature. The results are compared with those obtained with other popu…