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83 articles for “Monte Carlo”
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Research ArticleOpen accessIn the abstractPoisson Quasi-Maximum Likelihood Estimator-based CUSUM Test for Integer-Valued Time SeriesSangyeol LeeThis study considers the parameter change test for integer-valued time series models based on the Poisson quasi-maximum likelihood estimates. As a change point test, we consider the score vector-based CUSUM test and show that its limiting null distribution takes the form of a function of Brownian bridges. Moreover, the residual-based CUSUM tests are considered as alternatives. For evaluation, we conduct … …Journal of Mathematics and Statistics, Vol. 15, Issue 1 · 1 Oct 2019 · 7,656 accessesView PDFCite
Research ArticleOpen accessIn the abstractApplying Neural Network-Based Approach to Sickle Cell Disease-Related Pain ClassificationZacchaeus Omogbadegun, Israel Ogundele, Olufunke OladipupoSickle Cell Disease (SCD), an inherited Red Blood Cell (RBC) disorder, is characterized by anaemia, end-organ damage, unpredictable episodes of pain and early mortality. SCD affects 25% of people living in Central and West Africa causing life threatening “silent” strokes and lifelong damage. Nigeria accounts for 50% of SCD births worldwide (estimated 150,000 of 300,000 babies born with Symptomatic Sickle … …Journal of Computer Science, Vol. 15, Issue 6 · 28 Jun 2019 · 7,683 accessesView PDFCite
EditorialOpen accessIn the abstractAn Opportunity for the Agricultural Sector: The Renewable Energy SourcesRiccardo Testa, Salvatore TudiscaToday, among the most important issue for energy decisions by policymakers, there are security challenges and environmental impacts on climate change and economic aspects. Since the seventies, in fact, global warming and environmental issues have had an increasing importance in international debate, attracting the attention of several scientific studies (Landi and Benelli, 2016). Many of these studies denoted that over … …American Journal of Agricultural and Biological Sciences, Vol. 11, Issue 3 · 6 Sep 2016 · 8,098 accessesView PDFCite
Research ArticleOpen accessIn the abstractStatistical Inferences of the Rest Lifetimes of Ball Bearings' Residual Lifetimes Based on Rayleigh Residual Type II Censored DataGhassan K. Abufoudeh, Omar M. Bdair, Raed R. Abu AwwadIn this study, we consider statistical inference problems for the residual life data that come from the Rayleigh model based on type II censored data. Maximum likelihood and Bayesian approaches are used to estimate the scale and location parameters for the Rayleigh model, the Gibbs sampling procedure is used to draw Markov Chain Monte Carlo (MCMC) samples and MCMC samples … …Journal of Mathematics and Statistics, Vol. 12, Issue 3 · 1 Aug 2016 · 7,164 accessesView PDFCite
Research ArticleOpen accessIn the abstractEstimation 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 PDFCite
Research ArticleOpen accessIn the abstractStar Catalog Generation for Satellite Attitude Navigation Using Density Based ClusteringMuhammad Arif Saifudin, Bib Paruhum Silalahi, Imas Sukaesih SitanggangA new method to generate star catalog using density-based clustering is proposed. It identifies regions of a high star density by using Density-Based Spatial Clustering of Application with Noise (DBSCAN) algorithm. Reducing the number stars performed by storing the brightest star in each cluster. The brightest star and all non-clustered members are then stored as a navigation star candidate. Monte … …Journal of Computer Science, Vol. 11, Issue 12 · 1 Feb 2016 · 6,975 accessesView PDFCite
Research ArticleOpen accessIn the abstractA NOVEL ROBUST AND EFFICIENT TOOL FOR DETECTING HETEROSCEDASTICITYWei Xiong, Maozai TianOne of the greatest values of Quantile Regression (QR) is that it provides a good procedure in the sense that QR could be much more efficient and sometimes arbitrarily more efficient in recovering the mean function than the Least Squares (LS) even when without moment conditions. However, heteroscedasticity definitely causes conditional variances of parametric or nonparametric estimates of mean functions … …Journal of Mathematics and Statistics, Vol. 10, Issue 2 · 21 Mar 2014 · 6,662 accessesView PDFCite
Research ArticleOpen accessIn the abstractOPTIMIZATION MODEL OF SELECTIVE CUTTING FOR TIMBER HARVEST PLANNING BASED ON A SIMULATED ANNEALING APPROACHMunaisyah Abdullah, Salwani Abdullah, Abdul Razak Hamdan, Roslan IsmailAn optimization model for Timber Harvest Planning (THP) is used to form harvest areas with the objective of maximizing the tree harvest volume subject to harvest regulations. Most optimization models for THP currently in use are based on clear cutting and restricted to adjacency constraints to prevent the creation of large clear-cut openings in the forest. However, an optimization model … …Journal of Computer Science, Vol. 10, Issue 1 · 12 Nov 2013 · 7,318 accessesView PDFCite
Research ArticleOpen accessIn the abstractAsymptotic Giant Branch Stars Migration from the Central of the Milky Way Galaxy to our Sun’s Birthplace and its Relation with Silicon Carbide GrainsAhmad Hashem AbdelhadiSilicon carbide grains found in meteorites are peculiar in their age and isotopic ratios; they formed before the Sun was born and their isotopic signature indicates that they come from a different galactic region. This study aims to seek a possible paradigm for such richness and peculiarity through Monte Carlo simulation of scattering of Asymptotic Giant Branch (AGB) stars off … …Space Science International, Vol. 1, Issue 1 · 20 Jun 2013 · 7,058 accessesView PDFCite
Research ArticleOpen accessIn the abstractBayesian 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 · 6,662 accessesView PDFCite