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11 results for “squared error function”
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Research ArticleOpen accessEvery word in the titleOn Bayesian Premium Estimators for Gamma Lindley Model under Squared Error Loss Function and Linex Loss FunctionAhmed Sadoun, Halim Zeghdoudi, Fatma Zohra Attoui, Mohamed Riad RemitaWe consider the Gamma Lindley distribution (GaL) as the conditional distribution of (X|θ,γ), we focus on the estimation of the Bayesian premium under squared error loss function (symmetric) and linear-exponential (Linex) loss function (asymmetric), using informative priors (the Gamma prior). Because of its difficulty and non-linearity, we use a numerical approximation for computing the Bayesian premium. Finally, a simulation and … …Journal of Mathematics and Statistics, Vol. 13, Issue 3 · 23 Sep 2017 · 7,047 accessesView PDFCite
Research ArticleOpen accessIn the keywordsAn Efficient Unified K-Means Clustering Technique for Microarray Gene Expression DataP. Valarmathie, K. Dinakaran, T. RavichandranProblem statement: Using microarray techniques one could monitor the expressions levels of thousands of genes simultaneously. One challenge was how to derive meaningful insights into expressed data. This might be carried out by clustering techniques such as hierarchical and k-means, but most of the clustering techniques were largely heuristic in nature and are associated with some unresolved issues like how … …Journal of Computer Science, Vol. 7, Issue 7 · 28 Jun 2011 · 6,915 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA Modification of the Ridge Type Regression EstimatorsMoawad El-Fallah Abd El-SalamProblem statement: Many regression estimators have been used to remedy multicollinearity problem. The ridge estimator has been the most popular one. However, the obtained estimate is biased. Approach: In this stuyd, we introduce an alternative shrinkage estimator, called modified unbiased ridge (MUR) estimator for coping with multicollinearity problem. This estimator is obtained from Unbiased Ridge Regression (URR) in the same … …American Journal of Applied Sciences, Vol. 8, Issue 1 · 31 Jan 2011 · 7,641 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Adaptive Detail Preserving Modified Progressive Pca Thresholding Based Image DenoisingN. Anilkumar, S. Radhakrishnan, Shaik Syed Basha et al.Radiologists use medical imaging tools to assess the anatomy and function of interior organs. However, medical images are frequently distorted by various types of noise generated during the capture, transmission, and reconstruction operations, which can dramatically reduce image quality and hide critical diagnostic features. As a result, developing effective denoising algorithms that suppress noise while maintaining structural information remains a … …Journal of Computer Science, Vol. 22, Issue 8 · 8 Sep 2026 · 536 accessesView PDFCite
Research ArticleOpen accessIn the abstractBayesian 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
Research ArticleOpen accessIn the abstractA Suggested Nonparametric Bivariate Logistic Density Estimator with Application on the Productivity of Egyptian Wheat during 2019/2020Samah M. Abo-El-HadidIn this study, the nonparametric standard logistic density estimator, introduced by Abo-El-Hadid (2018), is extended to the bivariate case. The multiplicative standard logistic distribution is used as a kernel function to derive the bivariate kernel estimator. The statistical properties of the resulting estimator are studied, which are: The asymptotic bias, variance, Mean Squared Error (MSE) and Integrated Mean Squared Error … …Journal of Mathematics and Statistics, Vol. 17, Issue 1 · 27 May 2021 · 6,716 accessesView PDFCite
Research ArticleOpen accessIn the abstractTwo-Stage Estimation in Inverse Problems using Combined Wavelet Thresholding and Penalized Maximum LikelihoodRobert G Aykroyd, Hassan AljohaniInverse problems occur in a wide range of practical scientific investigations where the variables of interest are only observed indirectly, such as magnetic and seismic imaging in geophysics, electrical tomography in industrial process monitoring, or PET scanning in medicine. Linear inverse problems can be thought of as highly multivariate regression problems with strong multicollinearity where the aim is to interpret … …Journal of Mathematics and Statistics, Vol. 13, Issue 3 · 29 Sep 2017 · 7,928 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 abstractANALYSIS OF BAYESIAN CLASSIFIER ACCURACYFelipe Schneider Costa, Maria Marlene De Souza Pires, Silvia Modesto NassarThe naïve Bayes classifier is considered one of the most effective classification algorithms today, competing with more modern and sophisticated classifiers. Despite being based on unrealistic (naïve) assumption that all variables are independent, given the output class, the classifier provides proper results. However, depending on the scenario utilized (network structure, number of samples or training cases, number of variables), the … …Journal of Computer Science, Vol. 9, Issue 11 · 26 Sep 2013 · 8,379 accessesView PDFCite
Research ArticleOpen accessIn the abstractTwo Optimization Methods to Determine the Rate Constants of a Complex Chemical Reaction Using FORTRAN and MATLABAbdel-Latif Aboul Seoud, Lamiaa A.M. AbdallahProblem statement: For chemical reactions, the determination of the rate constants is both very difficult and a time consuming process. The aim of this research was to develop computer programs for determining the rate constants for the general form of any complex reaction at a certain temperature. The development of such program can be very helpful in the control of … …American Journal of Applied Sciences, Vol. 7, Issue 4 · 30 Apr 2010 · 8,050 accessesView PDFCite