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49 articles for “Bayesian method”

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Research ArticleOpen accessPhrase in the titleA Bayesian Method for Disentangling Dependent Structure of Epistatic InteractionJing Zhang, Qu Zhang, Darrin Lewis, Michael Q. ZhangProblem statement: We propose a Bayesian method (RBP) to recursively infer the independence structure of epistatic interactions in case-control study. Approach: Based on the results of BEAM2, RBP can powerfully detect the marginal and conditional independence within interacting SNPs even in the complicated interaction cases. Results: We did extensive simulations to test RBP and compare it with stepwise logistic regression. … …Current Research in Biostatistics, Vol. 2, Issue 1 · 13 Jan 2012 · 7,476 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleBayesian Methods for Ranking the Severity of Apnea among PatientsNur Zakiah Mohd Saat, Kamarulzaman Ibrahim, Abdul Aziz JemainProblem statement: Studies on apnea patients are often carried out based on data obtained from the sleep study. This data is quite scarce since high cost is required for conducting the study. Bayesian method is particularly suitable for analyzing limited data as it allows for updating of information by combining the current information with the prior belief. Approach: In this … …American Journal of Applied Sciences, Vol. 7, Issue 2 · 28 Feb 2010 · 7,550 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleHigh-Order Interactions in Rheumatoid Arthritis Detected by Bayesian Method using Genome-Wide Association Studies DataJing Zhang, Zheyang Wu, Chao Gao, Michael Q. ZhangProblem statement: In order to reveal the missing genetic component of Rheumatoid Arthritis (RA) susceptibility, we carried out a genome-wide high-order epistatic interaction study for RA. Approach: A powerful Bayesian strategy was applied to analyze the data of Genome-Wide Association Studies (GWAS) from the Welcome Trust Case Control Consortium (WTCCC), where 319 high-order interactions were found across the whole genome … …Current Research in Medicine, Vol. 3, Issue 1 · 30 Mar 2012 · 8,379 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleFuzzy Method for Online Learning of Bayesian Network ParametersMariana D.C. Lima, Silvia M. NassarIn learning problems, there are situations where training data is not fully available at the learning time. They are incrementally generated by time, defining a type of domain called online that has among its characteristics the possibility of data failure or even missing data. In Bayesian networks, learning is divided into two categories: structure (related to the graph of conditional … …Journal of Computer Science, Vol. 15, Issue 3 · 16 Mar 2019 · 7,498 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleHEURISTIC 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 · 7,054 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleA Comparison of the Bayesian and Other Methods for Estimation of Reliability Function for Burr-XII DistributionSafaa Ali Nasir, Nashaat Jaisam Al-AnberProblem statement: The Burr-XII distribution has been widely used especially in the modeling of life time event data. It provides a statistical model which has a wide variety of application in many areas and the main advantage is its ability in the context of life time event among other distributions. The conventional maximum likelihood method is the usual way to … …Journal of Mathematics and Statistics, Vol. 8, Issue 1 · 27 Dec 2011 · 7,852 accessesView PDFCite
Research ArticleOpen accessIn the keywordsHIDDEN MARKOV MODELS WITH COVARIATES FOR ANALYSIS OF DEFECTIVE INDUSTRIAL MACHINE PARTSPornpit Sirima, Premysl PokornyMonthly counts of industrial machine part errors are modeled using a two-state Hidden Markov Model (HMM) in order to describe the effect of machine part error correction and the amount of time spent on the error correction on the likelihood of the machine part to be in a &#34defective&#34 or &#34non-defective&#34 state. The number of machine parts errors were collected … …Journal of Mathematics and Statistics, Vol. 10, Issue 3 · 26 Jul 2014 · 6,859 accessesView PDFCite
Research ArticleOpen accessIn the keywordsBayesian Models for Time Series with Covariates, Trend, Seasonality, Autoregression and OutliersPitsanu Tongkhow, Nantachai KantananthaBayesian methods furnish an attractive approach to time series data analysis. This article proposes the forecasting models that can detect trend, seasonality, auto regression and outliers in time series data related to some covariates. Cumulative Weibull distribution functions for trend, dummy variables for seasonality, binary selections for outliers and latent autoregression for autocorrelated time series data are used for the … …Journal of Computer Science, Vol. 9, Issue 3 · 16 Apr 2013 · 6,653 accessesView PDFCite
Research ArticleOpen accessIn the keywordsBayesian 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 · 7,250 accessesView PDFCite
Research ArticleOpen accessIn the keywordsParameter Estimation for the Double Pareto DistributionFaris M. Al-AthariProblem statement: The double Pareto distribution appeared most often as model for variety of fields, including archaeology, biology, economics, environmental science, finance and physics. The distribution exhibits Paretian power-law behavior in both tails. The family of double Pareto distributions has recently been proposed for modeling growth rates such as annual gross domestic product, stock prices, foreign currency exchange rates and … …Journal of Mathematics and Statistics, Vol. 7, Issue 4 · 28 Oct 2011 · 8,674 accessesView PDFCite