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56 results for “Bayesian Approach”
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Research ArticleOpen accessPhrase in the titleTHE DEVELOPMENT OF AN EXPERT CAR FAILURE DIAGNOSIS SYSTEM WITH BAYESIAN APPROACHWidodo BudihartoIn this study we propose a model of an Expert System to diagnose a car failure and malfunction using Bayesian Approach. An expert car failure diagnosis system is a computer system that uses specific knowledge which is owned by an expert to resolve car problems. Our specific system consists of knowledge base and solution to diagnose failure of car from … …Journal of Computer Science, Vol. 9, Issue 10 · 5 Sep 2013 · 7,293 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleTilted Beta Binomial Linear Regression Model: A Bayesian ApproachEdilberto Cepeda-Cuervo, Maria Victoria Cifuentes-AmadoThis paper proposes new linear regression models to deal with overdispersed binomial datasets. These new models, called tilted beta binomial regression models, are defined from the tilted beta binomial distribution, proposed assuming that the parameter of the binomial distribution follows a tilted beta distribution. As a particular case of this regression models, we propose the beta rectangular binomial regression models, … …Journal of Mathematics and Statistics, Vol. 16, Issue 1 · 5 Jan 2020 · 8,788 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleA Distribution-Free Bayesian Approach for Indirect ComparisonsJohanna S. van Zyl, Jack D. TubbsThe objective of this paper is to consider an indirect comparison between treatments B and C when each have been compared directly to treatment A in separate studies. Problems of this type are common in Network Meta-Analysis (NMA). A commonly used method assumes that the underlying data, Y, are normally distributed and µ = E(Y) is the measure of clinical … …Journal of Mathematics and Statistics, Vol. 15, Issue 1 · 3 Jul 2019 · 6,691 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleSMOOTHING SPLINE IN SEMIPARAMETRIC ADDITIVE REGRESSION MODEL WITH BAYESIAN APPROACHRita Diana, I. Nyoman Budiantara, Purhadi, Satwiko DarmestoSemiparametric additive regression model is a combination of parametric and nonparametric regression models. The parametric components are not linear but following a polynomial pattern, while the nonparametric components are unknown pattern and assumed to be contained in the Sobolev space. The nonparametric components can be approximated by smoothing spline functions. In the development of smoothing spline, the classical statistical approach … …Journal of Mathematics and Statistics, Vol. 9, Issue 3 · 12 Jun 2013 · 7,254 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleRestructuring and Expanding Technology Acceptance Model Structural Equation Model and Bayesian ApproachMargaretha Ari Aggorowati, Nur Iriawan, Suhartono, Hasyim GautamaProblem statement: Technology Acceptance Model (TAM) is one of models that analyze user behavior to accept and use a new technology. SEM is the most statistical method which use in TAM analysis that provides the estimation strength of all hypothesized relationship between variables in a theoretical model. Consider to employing the standard SEM in TAM analysis which expected large data, … …American Journal of Applied Sciences, Vol. 9, Issue 4 · 10 Feb 2012 · 8,365 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleBayesian Approach to the Estimation of a Poisson Mean with Application to NBA Three Point AttemptsPatricia Pepple WilliamsonBayesian Credible Intervals are proposed for a Poisson mean. These intervals are compared to five classical confidence intervals found in the literature. A simulation study is performed to compare the procedures using two different criteria and it is attempted to determine which of the procedures performs best for various values of the parameter and sample size. Estimation of the number … …Journal of Mathematics and Statistics, Vol. 14, Issue 1 · 12 Nov 2018 · 7,095 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleBurr-X Model Estimate using Bayesian and non-Bayesian ApproachesAbdullah Y. Al-HossainThe present paper is aimed at developing Bayesian and Maximum Likelihood estimations (ML) of the Burr type-X model of distribution when data are gathered from Type-II cumulative censoring with binomial eliminations. The procedures for getting the (ML) evaluations of the parameters are examined. The Bayes technique to get both point and interval estimators of the parameters are illustrated. The expected … …Journal of Mathematics and Statistics, Vol. 12, Issue 2 · 6 May 2016 · 7,215 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleA Gene Selection Algorithm using Bayesian Classification ApproachAlok Sharma, Kuldip K. PaliwalIn this study, we propose a new feature (or gene) selection algorithm using Bayes classification approach. The algorithm can find gene subset crucial for cancer classification problem. Problem statement: Gene identification plays important role in human cancer classification problem. Several feature selection algorithms have been proposed for analyzing and understanding influential genes using gene expression profiles. Approach: The feature selection … …American Journal of Applied Sciences, Vol. 9, Issue 1 · 24 Nov 2011 · 8,312 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleLog data Approach to Acquisition of Optimal Bayesian Learner ModelChoo-Yee Ting, Somnuk Phon-AmnuaisukLog data provide valuable insight into observable behavioural patterns, which could be inferred to study a learner’s cognitive processes, levels of motivation and levels of knowledge acquisition. To date, most of the research work has been devoted to study the different methods to analyze and interpret log data. Little attention, however, has been given to use log data as a … …American Journal of Applied Sciences, Vol. 6, Issue 5 · 31 May 2009 · 7,082 accessesView PDFCite
Research ArticleOpen accessIn the keywordsBayesian Estimation for Lomax Distribution: A Comparison of Loss Functions Using Jeffreys PriorsHuda Mohammed AlomariThis study investigates the estimation of the shape parameter for the Lomax distribution using complete data. We compare the performance of the classical Maximum Likelihood Estimation (MLE) method against the Bayesian framework. Within the Bayesian approach, three distinct loss functions were utilized: the linear exponential (LINEX), general entropy, and weighted general entropy loss functions. The precision of these estimators was … …Journal of Mathematics and Statistics, Vol. 21, Issue 1 · 24 Dec 2025 · 2,643 accessesView PDFCite