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25 results for “Bayesian Methods”
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Research ArticleOpen accessIn the abstractAn Algorithm for Determining the Number of Mixture Components on the Bayesian Mixture Model Averaging for Microarray DataAni Budi Astuti, Nur Iriawan, Irhamah, Heri KuswantoThe major challenges on the statistical analysis of microarray data are the limited availability of samples, large number of measured variables and the complexity of distribution of the data obtained (e.g., multimodal). These phenomena could be considered in Bayesian method, used Bayesian Mixture Model (BMM) methods and Bayesian Model Averaging (BMA) methods. Modeling of Bayesian Mixture Model Averaging (BMMA) for … …Journal of Mathematics and Statistics, Vol. 11, Issue 2 · 28 Sep 2015 · 7,141 accessesView PDFCite
Research ArticleOpen accessIn the abstractSUPER RESOLUTION FOR EGYPTSAT-1 IMAGES WITH ERRATIC SHIFTA. H. Nasr, Gh.S. El-Tawel, A. K. HelmyThe key point of the Super-Resolution (SR) process is the accurate registration of the low resolution images, i.e., accurate measuring of the fixed shift between them, to obtain high resolution image. Due to certain malfunction, some Egyptsat-1 images have inconsistent sub-pixel shift. Therefore, in this study we propose a methodology to use this kind of shift for reconstructing a SR … …Journal of Computer Science, Vol. 10, Issue 7 · 17 Jun 2014 · 6,945 accessesView PDFCite
Research ArticleOpen accessIn the abstractHEURISTIC DISCRETIZATION METHOD FOR BAYESIAN NETWORKSMariana D.C. Lima, Silvia M. Nassar, Pedro Ivo R.B.G. Rodrigues et al.Bayesian Network (BN) is a classification technique widely used in Artificial Intelligence. Its structure is a Direct Acyclic Graph (DAG) used to model the association of categorical variables. However, in cases where the variables are numerical, a previous discretization is necessary. Discretization methods are usually based on a statistical approach using the data distribution, such as division by quartiles. In … …Journal of Computer Science, Vol. 10, Issue 5 · 18 Jan 2014 · 7,059 accessesView PDFCite
Research ArticleOpen accessIn the abstractBayesian Exploration of Multilocus Interactions on the Genome-Wide ScaleIvan Kozyryev, Jing ZhangProblem statement: Recent technological and scientific advances propelled the field of Genome-Wide Association Study (GWAS), which promises to be instrumental in linking many common complex diseases to their genetic origin. While so far such large-scale surveys have been moderately successful in identifying disease related genetic variants, much of disease heritability is still not accounted for by the discovered loci. There … …Current Research in Bioinformatics, Vol. 1, Issue 1 · 2 Jul 2012 · 7,410 accessesView PDFCite
Research ArticleOpen accessIn the abstractRestructuring 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 accessIn the abstractBayesian Changepoint Analysis of the Extreme Rainfall EventsWan Zawiah Wan Zin, Abdul Aziz Jemain, Kamarulzaman IbrahimProblem statement: This study assesses recent changes in extremes of annual rainfall in Peninsular Malaysia based on daily rainfall data for 50 rain-gauged stations over the period 1975-2004. Approach: Eight indices that represent the extreme events are defined and analyzed, which are extreme Dry Spell (XDS), extreme Rain-Sum (XRS), extreme wet-day intensities at 95% and 99% percentiles (I95 and I99), … …Journal of Mathematics and Statistics, Vol. 8, Issue 1 · 6 Feb 2012 · 7,255 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Comparative Study in Classification Techniques for Unsupervised Record Linkage ModelMohammadreza Ektefa, Fatimah Sidi, Hamidah Ibrahim et al.Problem statement: Record linkage is a technique which is used to detect and match duplicate records which are generated in data integration process. A variety of record linkage algorithms with different steps have been developed in order to detect such duplicate records. To find out whether two records are duplicate or not, supervised and unsupervised classification techniques are utilized in … …Journal of Computer Science, Vol. 7, Issue 3 · 7 Mar 2011 · 8,201 accessesView PDFCite
Research ArticleOpen accessIn the abstractStatistical Bayesian Learning for Automatic Arabic Text CategorizationBassam Al-Salemi, Mohd. Juzaiddin Ab AzizProblem statement: The rapid increasing of online Arabic documents necessitated applying Text Categorization techniques that are commonly used for English language to categorize them automatically. The complex morphology of Arabic language and its large vocabulary size make applying these techniques directly difficult and costly in time and effort. Approach: We have investigated Bayesian learning models in order to enhance Arabic … …Journal of Computer Science, Vol. 7, Issue 1 · 27 Dec 2010 · 8,406 accessesView PDFCite
Research ArticleOpen accessIn the abstractComparison of the Bayesian and Maximum Likelihood Estimation for Weibull DistributionAl Omari Mohammed Ahmed, Hadeel Salim Al-Kutubi, Noor Akma IbrahimProblem statement: The Weibull distribution has been widely used especially in the modeling of lifetime event data. It provides a statistical model which has a wide variety of applications in many areas, and the main advantage is its ability in the context of lifetime event, to provide reasonably accurate failure analysis and failure forecasts especially with extremely small samples. The … …Journal of Mathematics and Statistics, Vol. 6, Issue 2 · 30 Jun 2010 · 10,959 accessesView PDFCite
Research ArticleOpen accessIn the abstractModeling Heterogeneity in Phase II Clinical TrialsChristopher N. Barnes, Shesh N. RaiProblem statement: The common assumption in non-randomized Phase II clinical trials is a homogeneous population with homogeneous response. This assumption is at odds with many trials today; a heterogeneous response due to the existence of subgroups. Approach: In order to examine the effects of heterogeneity on the trial outcome, a systematic platform is developed to quantify the range and classes … …Current Research in Biostatistics, Vol. 1, Issue 1 · 30 Jun 2010 · 10,131 accessesView PDFCite