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  1. 1
    Estimation Of Weibull Parameters Using Simulated Annealing As Applied In Financial Data

    Estimation Of Weibull Parameters Using Simulated Annealing As Applied In Financial Data by Hamza, Abubakar

    Published 2023
    “…The finding reveals that the Weibull distribution is well-suited to describing the investment behaviour of the MPS based on the estimates via the SA algorithm. …”
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  2. 2
    Accuracy enhancement for zone mapping of a solar radiation forecasting based multi-objective model for better management of the generation of renewable energy

    Accuracy enhancement for zone mapping of a solar radiation forecasting based multi-objective model for better management of the generation of renewable energy by Ehteram M., Ahmed A.N., Fai C.M., Afan H.A., El-Shafie A.

    Published 2023
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  3. 3
    Dynamic Robust Bootstrap Algorithm for Linear Model Selection Using Least Trimmed Squares

    Dynamic Robust Bootstrap Algorithm for Linear Model Selection Using Least Trimmed Squares by Uraibi, Hassan Sami

    Published 2009
    “…They used the classical bootstrap method to estimate the bootstrap location and the scale parameters based on calculating the Mean of Squared Residual (MSR). …”
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  4. 4
    Slice sampler algorithm for generalized pareto distribution

    Slice sampler algorithm for generalized pareto distribution by Rostami, Mohammad, Adam, Mohd Bakri, Yahya, Mohamed Hisham, Ibrahim, Noor Akma

    Published 2018
    “…Based on the results, the slice sampler algorithm provides closer posterior mean values and shorter 95% quantile based credible intervals compared to the Metropolis-Hastings algorithm. …”
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  5. 5
    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
    “…We first look at the concentration parameter of von Mises distribution. The von Mises distribution is the most commonly used probability distribution of a circular random variable, and the concentration of a circular data set is measured using the mean resultant length. …”
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  6. 6
    Estimation of Transformers Health Index Based on Condition Parameter Factor and Hidden Markov Model

    Estimation of Transformers Health Index Based on Condition Parameter Factor and Hidden Markov Model by Selva A.M., Yahaya M.S., Azis N., Ab Kadir M.Z.A., Jasni J., Yang Ghazali Y.Z.

    Published 2023
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  7. 7
    Parameter estimation of K-distributed sea clutter based on fuzzy inference and Gustafson-Kessel clustering

    Parameter estimation of K-distributed sea clutter based on fuzzy inference and Gustafson-Kessel clustering by Davari, Atefeh, Marhaban, Mohammad Hamiruce, Mohd Noor, Samsul Bahari, Karimadini, Mohammad, Karimoddini, Ali

    Published 2011
    “…This paper proposes a novel approach to estimate the parameters of K-distribution, based on fuzzy Gustafson–Kessel clustering and fuzzy Takagi–Sugeno Kang modelling. …”
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  8. 8
    Estimation of transformers health index based on condition parameter factor and hidden Markov model

    Estimation of transformers health index based on condition parameter factor and hidden Markov model by Mohd Selva, Amran, Yahaya, Muhammad Sharil, Azis, Norhafiz, Ab Kadir, Mohd Zainal Abidin, Jasni, Jasronita, Yang Ghazali, Young Zaidey

    Published 2018
    “…First, the mean for HI in each year was computed and the transition probabilities for the condition data were obtained based on non-linear optimization technique. …”
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  9. 9
    Parameter estimation of the cure fraction based on BCH model using left-censored data with covariates.

    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
    “…The analysis is constructed by means of the exponential distribution in the case of left censoring and within the framework of the expectation maximization (EM) algorithm. …”
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  10. 10
    Extreme air pollutant data analysis using classical and Bayesian approaches

    Extreme air pollutant data analysis using classical and Bayesian approaches by Mohd Amin, Nor Azrita

    Published 2015
    “…This study started with the analysis of extreme PM10 data based on maximum likelihood estimation technique. …”
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  11. 11
    A new Gompertz-three-parameter-lindley distribution for modeling survival time data

    A new Gompertz-three-parameter-lindley distribution for modeling survival time data by Liang, Fei, Lu, Hezhi, Xi, Yuhang

    Published 2025
    “…Maximum likelihood estimators (MLEs) of unknown parameters are obtained via differential evolution algorithms, and simulation studies are conducted to evaluate the consistency of the MLEs. …”
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  12. 12
    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
    “…For the Weibull model with right censoring and unknown shape, the full conditional distribution for the scale and shape parameters are obtained via Gibbs sampling and Metropolis-Hastings algorithm from which the survival function and hazard function are estimated. …”
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  13. 13
    Air quality measurement using remote sensing and digital images processing techniques / Lim, H. S. … [et al.]

    Air quality measurement using remote sensing and digital images processing techniques / Lim, H. S. … [et al.] by Lim, H. S., Jafri, Mat, Abdullah, M. Z., Ahmad, A.N.

    Published 2004
    “…The relationship between the reflectance and the corresponding air quality data was determined using regression analysis. A new algorithm was developed for detecting air pollution from the digital camera images chosen based on the highest correlation coefficient, R and lowest root mean square error, RMS for PM10. …”
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  14. 14
    Em Approach on Influence Measures in Competing Risks Via Proportional Hazard Regression Model

    Em Approach on Influence Measures in Competing Risks Via Proportional Hazard Regression Model by Elfaki, Faiz. A. M.

    Published 2000
    “…From the simulation study for this particular case, we can conclude that the EM algorithm proved to be more superior in terms of mean value of parameter estimates, bias and root mean square error. …”
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  15. 15
    Covariance matrix analysis in simultaneous localization and mapping

    Covariance matrix analysis in simultaneous localization and mapping by Nur Aqilah, Othman

    Published 2016
    “…In EKF-based SLAM, measurement data are required at each time step to complete the estimation process. …”
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  16. 16
    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
    “…Thus coherent forecasting, which is based upon the k-step ahead conditional mean, median, mode and distribution, is considered. …”
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  17. 17
    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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  18. 18
    Vibration-based structural damage detection and system identification using wavelet multiresolution analysis / Seyed Alireza Ravanfar

    Vibration-based structural damage detection and system identification using wavelet multiresolution analysis / Seyed Alireza Ravanfar by Seyed Alireza, Ravanfar

    Published 2017
    “…This resulted in the high accuracy of the damage detection algorithm. The second proposed method seeks to identify damage in the structural parameters of linear and nonlinear systems. …”
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  19. 19
    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
    “…Methods for correcting the outliers and splitting the heterogeneous data are proposed. 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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  20. 20
    Optimization of hydropower reservoir system using genetic algorithm for various climatic scenarios

    Optimization of hydropower reservoir system using genetic algorithm for various climatic scenarios by Tayebiyan, Aida

    Published 2015
    “…The first step, ANN was calibrated and validated by using daily observed evapotranspiration, rainfall, and stream flow (2003-2012). In order to estimate daily evapotranspiration, daily observed Min and Max temperature was used in the estimation based on Hargreaves-Samani equation. …”
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