Search Results - (( a distribution based algorithm ) OR ( parametric estimation model algorithm ))*

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  1. 1

    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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    Rank regression for modeling bus dwell time in the presence of censored observations by Karimi, Mostafa, Ibrahim, Noor Akma

    Published 2019
    “…An iterative algorithm is introduced that involves a monotone estimating function of the model parameter, and its minimization is a computationally simple optimization problem. …”
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    Article
  5. 5

    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
    “…Design/methodology/approach – The parameters of the models have been estimated by method of maximum likelihood based on EM algorithm. …”
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  6. 6

    Parametric Study Of Instantaneous Heat Transfer Based on Multidimensional Model in Direct-Injection Hydrogen-Fueled Engine by Hamada, Khalaf I., M. M., Rahman, A. Rashid, A. Aziz

    Published 2013
    “…It is clear that the developed models are powerful tools for estimating the heat transfer of the hydrogen-fueled engine. …”
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  7. 7

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

    Published 2004
    “…A generated data where the failure times are taken as exponentially distributed are used to further compare these two parametric models. …”
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    Parameter estimation of the cure fraction based on BCH model using left-censored data with covariates. by I. Aljawadi, Bader Ahnad, Abu Bakar, Mohd Rizam, Ibrahim, Noor Akma, Midi, Habshah

    Published 2011
    “…In this paper, we propose an analytical approach for parametric estimation of the cure fraction in cancer clinical trials based on the bounded cumulative hazard (BCH) model with covariates involved in the data set. …”
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  9. 9

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

    Published 2017
    “…Asa consequence of this, it can be used suitably for censored data. Based on the problem stated, we develop a new model using the method of confounding the existing parametric models by adopting the BX model as the baseline distribution. …”
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    Turnbull versus Kaplan-Meier estimators of cure rate estimation using interval censored data by Aljawadi, Bader Ahmad I., Abu Bakar, Mohd Rizam, Ibrahim, Noor Akma

    Published 2012
    “…A comparison of the cure rate estimation based on the two estimators was done through a simulation study.…”
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  11. 11

    Fault Detection Relevant Modeling of an Industrial Gas Turbine based on Neuro-Fuzzy Approach by Alemu Lemma, Tamiru, Mohd Hashim, Fakhruldin, Rangkuti, Chalillullah

    Published 2010
    “…Structure and network weights for the NF model are determined by a synergetic approach – Data clustering and Gradient Descent algorithm. …”
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  12. 12

    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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    Channel Modeling and Direction-of-Arrival Estimation in Mobile Multiple-Antenna Communication Systems by Ravari, Arastoo Rostami

    Published 2005
    “…Low-complexity spectral-based estimators are used for the estimation of direction and spatial spread of the distributed source by employing the proposed channel model for simulation. …”
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    Thesis
  14. 14

    A parametric mixture model of three different distributions: An approach to analyse heterogeneous survival data by Mohammed, Yusuf Abbakar, Yatim, Bidin, Ismail, Suzilah

    Published 2014
    “…A parametric mixture model of three different distributions is proposed to analyse heterogeneous survival data.The maximum likelihood estimators of the postulated parametric mixture model are estimated by applying an Expectation Maximization Algorithm (EM) scheme.The simulations are performed by generating data, sampled from a population of three component parametric mixture of three different distributions. …”
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    A simulation study of a parametric mixture model of three different distributions to analyze heterogeneous survival data by Mohammed, Yusuf Abbakar, Yatim, Bidin, Ismail, Suzilah

    Published 2013
    “…In this paper a simulation study of a parametric mixture model of three different distributions is considered to model heterogeneous survival data.Some properties of the proposed parametric mixture of Exponential, Gamma and Weibull are investigated.The Expectation Maximization Algorithm (EM) is implemented to estimate the maximum likelihood estimators of three different postulated parametric mixture model parameters.The simulations are performed by simulating data sampled from a population of three component parametric mixture of three different distributions, and the simulations are repeated 10, 30, 50, 100 and 500 times to investigate the consistency and stability of the EM scheme.The EM Algorithm scheme developed is able to estimate the parameters of the mixture which are very close to the parameters of the postulated model.The repetitions of the simulation give parameters closer and closer to the postulated models, as the number of repetitions increases, with relatively small standard errors.…”
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    An intelligent framework for modelling and active vibration control of flexible structures by Mohd. Hashim, Siti Zaiton

    Published 2004
    “…Parametric approaches include linear parametric modelling of the system using recursive least squares (RLS) and genetic algorithms (GAS); and non-parametric approaches include multi-layered perceptron neural networks (MLP-NNs) and adaptive neuro-fuzzy inference systems (ANFIS) are employed. …”
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    GEE-smoothing spline in semiparametric model with correlated nominal data by Ibrahim, Noor Akma, Suliadi

    Published 2010
    “…We use profile algorithm in the estimation of both parametric and nonparametric components. …”
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    Semiparametric binary model for clustered survival data by Arlin, Rifina, Ibrahim, Noor Akma, Arasan, Jayanthi, Abu Bakar, Mohd Rizam

    Published 2014
    “…A backfitting algorithm is used in the derivation of the estimating equation for the parametric and nonparametric components of a semiparametric binary covariate model. …”
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