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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
    “…However, the selection of the most suitable estimators is still a challenging task. The present study proposes a simulated annealing algorithm (SA) in estimating the parameters of Weibull distribution with application to modified internal rate of return data (MIRR).The objective is to examine the investment potential of the shari’ah compliance companies of the Malaysia property sector (MPS). …”
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  2. 2
    Improved performance in distributed estimation by convex combination of DNSAF and DNLMS algorithms

    Improved performance in distributed estimation by convex combination of DNSAF and DNLMS algorithms by Ahmad Pouradabi, Amir Rastegarnia, Azam Khalili, Ali Farzamnia

    Published 2022
    “…In diffusion estimation of distributed networks two characteristic parameters are crucial, the speed of convergence and steady-state error. …”
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  3. 3
    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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  4. 4
    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
    “…The Ordinary Least Squares (OLS) method is often used to estimate the parameters of a linear model. Under certain assumptions, the OLS estimates are the best linear unbiased estimates. …”
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  5. 5
    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
    “…Moreover, the slice sampler algorithm presents a higher level of stationarity in terms of the scale and shape parameters compared with the Metropolis-Hastings algorithm. …”
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  6. 6
    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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  7. 7
    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
    Conference Paper
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  8. 8
    Parameter-driven count time series models / Nawwal Ahmad Bukhari

    Parameter-driven count time series models / Nawwal Ahmad Bukhari by Nawwal , Ahmad Bukhari

    Published 2018
    “…Simulation shows that MCEM algorithm and particle method are useful for the parameter estimation of the Poisson model. …”
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  9. 9
    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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  10. 10
    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
    “…This paper presents a study to estimate future Health Index (HI) of transformer population based on Hidden Markov Model (HMM). …”
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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
    “…In this paper, a new survival distribution is introduced. It is a mixture of the Gompertz distribution and three-parameter-Lindley distribution. …”
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  12. 12
    Kernel and multi-class classifiers for multi-floor wlan localisation

    Kernel and multi-class classifiers for multi-floor wlan localisation by Abd Rahman, Mohd Amiruddin

    Published 2016
    “…Unlike the classical kNN algorithm which is a regression type algorithm, the proposed localisation algorithms utilise machine learning classification for both linear and kernel types. …”
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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 newly developed algorithm produced a high degree of accuracy with the correlation coefficient (R) of 0.9001 and the root-mean-square error (RMS) of 5.1008 µg/m³ for PM10. …”
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  14. 14
    Statistical approach on grading: mixture modeling

    Statistical approach on grading: mixture modeling by Md. Desa, Zairul Nor Deana

    Published 2006
    “…A solution to this problem is using the Markov Chain Monte Carlo method namely Gibbs sampler algorithm. …”
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  15. 15
    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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  16. 16
    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
    “…MTM algorithm is an extension of MH algorithm, designed to improve the convergence of MH algorithm by performing parallel computation. …”
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  17. 17
    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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  18. 18
    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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  19. 19
    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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  20. 20
    Machine learning for mapping and forecasting poverty in North Sumatera: a datadriven approach

    Machine learning for mapping and forecasting poverty in North Sumatera: a datadriven approach by Marpaung, Faridawaty, Ramadhani, Fanny, Dinata, Dewan

    Published 2024
    “…Poverty prediction was conducted using a random forest (RF) algorithm and poverty mapping was conducted using the K-Means algorithm. …”
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