Search Results - weibull estimation methods algorithm

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  1. 1
    Bayesian survival and hazard estimates for Weibull regression with censored data using modified Jeffreys prior

    Bayesian survival and hazard estimates for Weibull regression with censored data using modified Jeffreys prior by Ahmed, Al Omari Mohammed

    Published 2013
    “…Thus we develop an approach to accommodate the covariate terms in the Jeffreys and Modified of Jeffreys prior by employingGauss quadrature method. Subsequently, we use Markov Chain Monte Carlo (MCMC) method in the Bayesian estimator of the Weibull distributionand Weibull regression model with shape unknown. …”
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  2. 2
    An analytical approach on parametric estimation of cure fraction based on weibull distribution using interval censored data.

    An analytical approach on parametric estimation of cure fraction based on weibull distribution using interval censored data. by I. Aljawadi , Bader Ahmad, Abu Bakar, Mohd Rizam, Ibrahim, Noor Akma

    Published 2011
    “…Maximum likelihood estimation (MLE) method is proposed to estimate the parameters within the framework of expectation-maximization (EM) algorithm, Newton Raphson method also employed. …”
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  3. 3
    Non-Parametric and Parametric Estimations of Cure Fraction Using Right-and Interval-Censored Data

    Non-Parametric and Parametric Estimations of Cure Fraction Using Right-and Interval-Censored Data by Aljawdi, Bader

    Published 2011
    “…In this thesis, we considered two methods via the expectation maximization (EM) algorithm for cure rate estimation based on the BCH model using the two censoring types common to cancer clinical trials; namely, right and interval censoring. …”
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  4. 4
    Competing risks for reliability analysis using Cox’s model

    Competing risks for reliability analysis using Cox’s model by Mohamed Elfaki, Faiz Ahmed, Daud, Isa, Ibrahim, Nor Azowa, Abdullah, M. Y., Usman, Mustofa

    Published 2007
    “…This paper seeks to show that, with a large sample size based on expectation maximization (EM) algorithm, both models give similar results. Design/methodology/approach – The parameters of the models have been estimated by method of maximum likelihood based on EM algorithm. …”
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  5. 5
    Parametric and Semiparametric Competing Risks Models for Statistical Process Control with Reliability Analysis

    Parametric and Semiparametric Competing Risks Models for Statistical Process Control with Reliability Analysis by Mohamed Elfaki, Faiz Ahmed

    Published 2004
    “…The Expectation Maximization (EM) algorithm is utilized to obtain the estimate of the parameters in the models. …”
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  6. 6
    Parameter estimation of Kumaraswamy Burr type X models based on cure models with or without covariates

    Parameter estimation of Kumaraswamy Burr type X models based on cure models with or without covariates by Yusuf, Madaki Umar

    Published 2017
    “…In this thesis, we considered two methods via the classical maximum likelihood estimation (MLE) and the Bayes estimation using the Gibbs sampling (G-S) algorithm to estimate the parameters of BKBX, KBX and Beta-Weibull (BWB) models. …”
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  7. 7
    Reliability assessment of power system generation adequacy with wind power using population-based intelligent search methods

    Reliability assessment of power system generation adequacy with wind power using population-based intelligent search methods by Kadhem, Athraa Ali

    Published 2017
    “…This model took into consideration the seasonal wind speed variation during the year, in the format of the combined method comprising the Weibull model with artificial neural network (ANN), so that the forecasting errors of wind values would be lower than those generated by using only the Weibull model. …”
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  8. 8
    Power prediction using the wind turbine power curve and data-driven approaches / Ehsan Taslimi Renani

    Power prediction using the wind turbine power curve and data-driven approaches / Ehsan Taslimi Renani by Ehsan Taslimi , Renani

    Published 2018
    “…In this method, firstly, Weibull density function is utilized to model the wind speed and then several methods are applied to estimate the parameters of the wind speed distribution. …”
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  9. 9
    A memory-guided Jaya algorithm to solve multi-objective optimal power flow integrating renewable energy sources

    A memory-guided Jaya algorithm to solve multi-objective optimal power flow integrating renewable energy sources by Ahmadipour M., Ali Z., Ramachandaramurthy V.K., Ridha H.M.

    Published 2025
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  10. 10
    Some families of count distributions for modelling zero-inflation and dispersion / Low Yeh Ching

    Some families of count distributions for modelling zero-inflation and dispersion / Low Yeh Ching by Low, Yeh Ching

    Published 2016
    “…A Monte Carlo simulation technique is examined and employed to overcome the computational issues arising from the intractability of the probability mass function of some mixed Poisson distributions. For parameter estimation, the simulated annealing global optimization routine and an EM-algorithm type approach for maximum likelihood estimation are studied. …”
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  11. 11
    Optimization of multipurpose reservoir operation using evolutionary algorithms / Mohammed Heydari

    Optimization of multipurpose reservoir operation using evolutionary algorithms / Mohammed Heydari by Mohammed , Heydari

    Published 2017
    “…One of the main problems of this method is premature convergence and to improve this problem, the compound of the particle swarm algorithm and genetic algorithm were evaluated. …”
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