25 results for “Bayesian Methods”

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Research ArticleOpen accessIn the abstractLog 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 PDF Cite

Research ArticleOpen accessIn the abstractA Comparison of Spatio-Temporal Bayesian Models for Reconstruction of Rainfall Fields in a Cloud Seeding ExperimentSujit k. sahu, Giovanna Jona Lasinio, Arianna orasi, Kanti V. MardiaIn response to the drought experienced in Southern Italy a rain seeding project has been setup and developed during the years 1989-1994. The initiative was taken with the purpose of applying existing methods of rain enhancement technology to regions of south Italy including Puglia. The aim of this study is to provide statistical support for the evaluation of the experimental … …Journal of Mathematics and Statistics, Vol. 1, Issue 4 · 31 Dec 2005 · 6,813 accessesView PDF Cite

Research ArticleOpen accessIn the abstractCOMBINING LONG MEMORY AND NONLINEAR MODEL OUTPUTS FOR INFLATION FORECASTHeri Kuswanto, Irhamah, Laylia AfidahLong memory and nonlinearity have been proven as two models that are easily to be mistaken. In other words, nonlinearity is a strong candidate of spurious long memory by introducing a certain degree of fractional integration that lies in the region of long memory. Indeed, nonlinear process belongs to short memory with zero integration order. The idea of the forecast … …Journal of Mathematics and Statistics, Vol. 10, Issue 3 · 7 Jul 2014 · 6,984 accessesView PDF Cite

Research ArticleOpen accessAll words, across the recordDevelopment of Big Data Classifier for Biomedicine Early Diagnosis: An Experimental Approach Using Machine Learning MethodsMa Beth Solas Concepcion, Bobby Dioquino Gerardo, Frank Ibañez Elijorde et al.In the fast-phase world, data availability is abundant due to a rapid adaptation increase of big data technologies. Large amounts of data have been generated and collected at an unprecedented speed and scale, introducing a revolution in medical research practices for biomedicine informatics. Thus, there is an immense demand for statistically rigorous approaches, especially in the medical diagnosis discipline. Therefore, … …Journal of Computer Science, Vol. 20, Issue 4 · 1 Feb 2024 · 5,516 accessesView PDF Cite

Research ArticleOpen accessAll words, across the recordEstimation for Unknown Parameters of the Burr Type-XII Distribution Based on an Adaptive Progressive Type-II Censoring SchemeMontaser M. AmeinIn this study, the Maximum Likelihood Estimation (MLE) and Bayes estimation are exploited to make interval estimation based on adaptive progressive Type-II censoring for the Burr Type-XII distribution. Explicit form for the parameters of Bayes estimator doesn’t exist, so, Markov Chain Monte Carlo (MCMC) method is used as approximation to find posterior mean under squared error loss function. Real data … …Journal of Mathematics and Statistics, Vol. 12, Issue 2 · 29 Apr 2016 · 7,310 accessesView PDF Cite