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  1. 1
    Parameter estimation and outlier detection for some types of circular model / Siti Zanariah binti Satari

    Parameter estimation and outlier detection for some types of circular model / Siti Zanariah binti Satari by Satari, Siti Zanariah

    Published 2015
    “…This study focuses on the parameter estimation and outlier detection for some types of the circular model. …”
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  2. 2
    A simulation study of a parametric mixture model of three different distributions to analyze heterogeneous survival data

    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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  3. 3
    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
    “…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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  4. 4
    Dynamic robust bootstrap method based on LTS estimators

    Dynamic robust bootstrap method based on LTS estimators by Midi, Habshah, Uraibi, Hassan Sami, Al-Talib, Bashar Abdul Aziz Majeed

    Published 2009
    “…The applications of bootstrap methods in regression analysis have drawn much attention to the statistics practitioners because of some practical reasons. In order to make reliable inferences about the parameters of a model, require that the parameter estimates are normally distributed. …”
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  5. 5
    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
    “…Then, a series of simulation studies was conducted to evaluate the performance of the proposed estimation approaches. …”
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  6. 6
    A generator of cauchy-distributed time series with specific Hurst index

    A generator of cauchy-distributed time series with specific Hurst index by Estrada-Vargas, Leopoldo, Toral-Cruz, Homero, Pathan, Al-Sakib Khan

    Published 2011
    “…The proposed algorithm consists of an inverse cumulative distribution function (ICDF) transformation, a wavelet-analysis synthesis and, finally, a linear transformation. …”
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  7. 7
    Application of image processing and adaptive neuro-fuzzy system for estimation of the metallurgical parameters of a flotation process

    Application of image processing and adaptive neuro-fuzzy system for estimation of the metallurgical parameters of a flotation process by Jahedsaravani, A., Massinaei, Mohammad, Marhaban, Mohammad Hamiruce

    Published 2016
    “…The authors have already developed some reliable algorithms for measurement of the froth surface visual parameters such as bubble size distribution, froth color, velocity and stability. …”
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  8. 8
    Statistical modelling of time series of counts for a new class of mixture distributions / Khoo Wooi Chen

    Statistical modelling of time series of counts for a new class of mixture distributions / Khoo Wooi Chen by Khoo, Wooi Chen

    Published 2016
    “…The iv score functions and information matrix have been derived to measure the asymptotic standard errors and to analyze the variance-covariance relationship among the parameters. Parameter estimation with the maximum likelihood estimation via the Expectation-Maximization algorithm is discussed and compared with the conditional least squares method. …”
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  9. 9
    Distributed Adaptive Leader-following control for multi-agent multi-degree manipulators with Finite-Time guarantees

    Distributed Adaptive Leader-following control for multi-agent multi-degree manipulators with Finite-Time guarantees by Mahyuddin, Muhammad Nasiruddin, Herrmann, Guido, Lewis, Frank L.

    Published 2013
    “…A robust distributed adaptive leader-following control for multi-degree-of-freedom (multi-DOF) robot manipulator-type agents is proposed to guarantee finite-time convergence for leader-following tracking and parameter estimation via agent-based estimation and control algorithms. …”
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  10. 10
    Class binarization with self-adaptive algorithm to improve human activity recognition

    Class binarization with self-adaptive algorithm to improve human activity recognition by Zainudin, Muhammad Noorazlan Shah

    Published 2018
    “…To enhance the selection of most highly ranking features, irrelevant features are ‘pruned’ based on determined boundary threshold. In order to estimate the quality of ‘pruned’ features, self-adaptive DE algorithm is proposed. …”
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  11. 11
    Channel Modeling and Direction-of-Arrival Estimation in Mobile Multiple-Antenna Communication Systems

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

    Published 2005
    “…The second part of the thesis deals with channel parameter estimation of distributed scattering sources. …”
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  12. 12
    Machine condition monitoring and fault diagnosis using spectral analysis techniques

    Machine condition monitoring and fault diagnosis using spectral analysis techniques by Salami, Momoh Jimoh Eyiomika, Abdul Muthalif, Asan Gani, Pervez, T.

    Published 2001
    “…Furthermore the estimated AR model parameters and the distribution of the singular values can be used in conjunction with the spectral peaks in making comparison between healthy and faulty conditions. …”
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  13. 13
    A new metaphor-less algorithms for the photovoltaic cell parameter estimation

    A new metaphor-less algorithms for the photovoltaic cell parameter estimation by Premkumar M., Babu T.S., Umashankar S., Sowmya R.

    Published 2023
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  14. 14
    Modelling and Forecasting the Kuala Lumpur Composite Index Rate of Returns Using Generalised Autoregressive Conditional Heteroscedasticity Models

    Modelling and Forecasting the Kuala Lumpur Composite Index Rate of Returns Using Generalised Autoregressive Conditional Heteroscedasticity Models by Abdul Muthalib, Maiyastri

    Published 2004
    “…The EM algorithm is applied to split the heterogeneous data, and the estimated parameters are used to correct the outlying data using the Mahalanobis Distance. …”
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  15. 15
    Artificial Bee Colony algorithm in estimating kinetic parameters for yeast fermentation pathway

    Artificial Bee Colony algorithm in estimating kinetic parameters for yeast fermentation pathway by Ahmad Muhaimin, Ismail, Muhammad Akmal, Remli, Yee Wen, Choon, Nurul Athirah, Nasarudin, Norsyahidatul Nazirah, Ismail, Mohd Arfian, Ismail, Mohd Saberi, Mohamad

    Published 2023
    “…Parameter estimation is a challenging task in the biological process due to the complexity and nonlinearity of the model. …”
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  16. 16
    Enhanced segment particle swarm optimization for large-scale kinetic parameter estimation of escherichia coli network model

    Enhanced segment particle swarm optimization for large-scale kinetic parameter estimation of escherichia coli network model by Mohammed Adam, Kunna Azrag

    Published 2021
    “…However, the large-scale kinetic parameters estimation using optimization algorithms is still not applied to the main metabolic pathway of the E. coli model, and they’re a lack of accuracy result been reported for current parameters estimation using this approach. …”
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  17. 17
    An Improved Scatter Search Algorithm for Parameter Estimation in Large-Scale Kinetic Models of Biochemical Systems

    An Improved Scatter Search Algorithm for Parameter Estimation in Large-Scale Kinetic Models of Biochemical Systems by Muhammad Akmal, Remli, Mohd Saberi, Mohamad, Safaai, Deris, Sinnott, Richard O., Suhaimi, Napis

    Published 2019
    “…Methods: This paper proposes an improved scatter search algorithm to address the challenging parameter estimation problem. …”
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  18. 18
    Estimation in spot welding parameters using genetic algorithm

    Estimation in spot welding parameters using genetic algorithm by Lukman, Hafizi

    Published 2007
    “…Genetic algorithm (GA) used as parameter estimation method for a model structure. …”
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  19. 19
    Semiparametric inference procedure for the accelarated failure time model with interval-censored data

    Semiparametric inference procedure for the accelarated failure time model with interval-censored data by Karimi, Mostafa

    Published 2019
    “…A computationally simple two-step iterative algorithm, called estimationapproximation algorithm, is introduced for estimating the parameters of the model on the basis of the rank estimators. …”
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  20. 20
    An enhanced segment particle swarm optimization algorithm for kinetic parameters estimation of the main metabolic model of Escherichia coli

    An enhanced segment particle swarm optimization algorithm for kinetic parameters estimation of the main metabolic model of Escherichia coli by Mohammed Adam, Kunna, Tuty Asmawaty, Abdul Kadir, Muhammad Akmal, Remli, Noorlin, Mohd Ali, Kohbalan, Moorthy, Noryanti, Muhammad

    Published 2020
    “…In addition, building a kinetic model requires the estimation of the kinetic parameters, but kinetic parameters estimation in kinetic modeling is a difficult task due to the nonlinearity of the model. …”
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