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32 results for “likelihood method-of-estimation”
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Research ArticleOpen accessIn the keywordsEstimating the Claim Severity Distribution using Variable Neighborhood SearchKunjira Kingphai, Samruam ChongcharoenIn this study, Variable Neighborhood Search (VNS) is utilized to estimate the parameters of actual motor insurance claims data set and compared them obtained by the Moment Estimation Methods (MOM) and Maximum likelihood Estimation Method (MLE) which are known as a conscientious method. Then, the Kolmogorov-Smirnov test (K-S) is used to show how well the selected distribution fits the actual … …American Journal of Applied Sciences, Vol. 13, Issue 12 · 19 Dec 2016 · 7,326 accessesView PDFCite
Research ArticleOpen accessIn the keywordsEffects of Students' Beliefs on Mathematics and Achievement of University Students: Regression Analysis ApproachVelo Suthar, Rohani Ahmad TarmiziProblem statement: At present, after almost more than 20-decades, Malaysia can boast of a solid national philosophy of education, despite tremendous struggles and hopes. The professional learning opportunities are necessary to enhance, support and sustain student's mathematics achievement. Approach: Empirical evidence had shown that student's belief in mathematics is crucial in meeting career aspiration. In addition mathematical beliefs are closely … …Journal of Social Sciences, Vol. 6, Issue 2 · 30 Jun 2010 · 8,016 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 · 2,635 accessesView PDFCite
Research ArticleOpen accessIn the abstractA New Family: Σh DistributionsYasser Mohamed Amer, Rania Mustafa ShalabiIn this study, a new method is proposed for generating families of the sum of the hazard functions for two distributions named the Σh distributions. This new family will help in the application of a wider range of life time data. Many new distributions, which are members of the family, are presented with emphasis on the Σh Exponential-Lomax distribution. Details … …Journal of Mathematics and Statistics, Vol. 17, Issue 1 · 7 Jan 2021 · 7,281 accessesView PDFCite
Research ArticleOpen accessIn the abstractUnivariate Generalized Additive Models for Simulated Stationary and Non-Stationary Generalized Pareto DistributionMostafa Behzadi, Mohd Bakri Adam, Anwar FitriantoGeneralized additive models as a predictor in regression approaches, are made up over cubic spline basis and penalized regression splines. Despite of linear predictor in GLM, generalized additive models use a sum of smooth functions of covariates as a predictor. The data which are used in this study have generalized Pareto distribution and have been simulated by inversion method. The … …Journal of Mathematics and Statistics, Vol. 13, Issue 2 · 3 Jun 2017 · 7,430 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 · 7,306 accessesView PDFCite
Research ArticleOpen accessIn the abstractProportional Hazard Inverse Weibull Distribution and Associated InferenceSuja M. Aboukhamseen, Mohamed E. Ghitany, Ramesh C. GuptaIn this study, we have considered the proportional hazard version of the inverse Weibull distribution. It has been shown that the density and hazard rate functions are unimodal and the mean residual life function is bathtub shaped. For the considered model, many functions of the parameters, such as the mean, variance, coefficient of variation and the critical points of the … …Journal of Mathematics and Statistics, Vol. 12, Issue 2 · 18 Apr 2016 · 7,385 accessesView PDFCite
Research ArticleOpen accessIn the abstractHIDDEN 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 abstractPOISSON-WEIGHTED EXPONENTIAL UNIVARIATE VERSION AND REGRESSION MODEL WITH APPLICATIONSHossein Zamani, Noriszura Ismail, Pouya FaroughiThis study introduces a new two-parameter mixed Poisson distribution, namely Poisson-Weighted Exponential (P-WE), which is obtained by mixing Poisson distribution with a new class of weighted exponential distribution. The new P-WE distribution provides a more flexible alternative for modelling over dispersed count data compared to Poisson distribution. The estimation procedures of P-WE distribution via method of moments and maximum likelihood … …Journal of Mathematics and Statistics, Vol. 10, Issue 2 · 8 Mar 2014 · 7,341 accessesView PDFCite
Research ArticleOpen accessIn the abstractLENGTH BIASED BETA-PARETO DISTRIBUTION AND ITS STRUCTURAL PROPERTIES WITH APPLICATIONNareerat Nanuwong, Winai BodhisuwanThe concept of length biased distribution can be employed in development of proper models for lifetime data. Its method is adjusting the original probability density function from real data and the expectation of those data. This adjustment can bring about to correct conclusions of models. Therefore, we introduced the Length Biased Beta-Pareto (LBBP) distribution, so-called a new generalized of Pareto … …Journal of Mathematics and Statistics, Vol. 10, Issue 1 · 11 Jan 2014 · 7,237 accessesView PDFCite