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  1. 1
    Modeling Earthquake Bond Prices with Correlated Dual Trigger Indices and the Approximate Solution Using the Monte Carlo Algorithm

    Modeling Earthquake Bond Prices with Correlated Dual Trigger Indices and the Approximate Solution Using the Monte Carlo Algorithm by Riza Andrian Ibrahim, Sukono, Herlina Napitupulu, Rose Irnawaty Ibrahim

    Published 2025
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  2. 2
    Hierarchical Bayesian estimation for stationary autoregressive models using reversible jump MCMC algorithm

    Hierarchical Bayesian estimation for stationary autoregressive models using reversible jump MCMC algorithm by Suparman, S., Rusiman, Mohd Saifullah

    Published 2018
    “…The posterior distribution has a complex shape so that the Bayesian estimator is not analytically determined. The reversible jump Markov Chain Monte Carlo (MCMC) algorithm is proposed to obtain the Bayesian estimator. …”
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  3. 3
    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
    “…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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    Thesis
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  4. 4
    Simple algorithm for estimating the effects of reinforcement loadings and arrangements on composite properties

    Simple algorithm for estimating the effects of reinforcement loadings and arrangements on composite properties by Wan Ibrahim, W. M. A, Yeoh, C. K., Teh, P.L., Khairel Rafezi, Ahmad, Ruhiyuddin , Mohd Zaki

    Published 2010
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  5. 5
    Real-time algorithmic music composition application.

    Real-time algorithmic music composition application. by Yap, Alisa Yi Hui

    Published 2022
    “…In addition, the system also utilises JavaFx and jFugue for its graphical user interface and music programming respectively. …”
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  6. 6
    Slice sampling technique in Bayesian extreme of gold price modelling

    Slice sampling technique in Bayesian extreme of gold price modelling by Rostami, Mohammad, Adam, Mohd Bakri, Ibrahim, Noor Akma, Yahya, Mohamed Hisham

    Published 2013
    “…We compared the accuracy of slice sampling with other methods for a Gumbel model. This study revealed that slice sampling algorithm offers more accurate and closer estimates with less RMSE than other methods. …”
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  7. 7
    Application-Programming Interface (API) for Song Recognition Systems

    Application-Programming Interface (API) for Song Recognition Systems by Murtadha Arif Sahbudin, Chakib Chaouch, Salvatore Serrano

    Published 2024
    “…In addition the implementation is done by algorithm using Java’s programming language, executed through an application developed in the Android operating system. …”
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  8. 8
    Estimation of the Epidemiological Parameter for the COVID-19 Outbreak

    Estimation of the Epidemiological Parameter for the COVID-19 Outbreak by Muhammad Fahmi, Ahmad Zuber, Norhayati, Rosli, Noryanti, Muhammad

    Published 2024
    “…In this study, we propose a Metropolis-Hastings algorithm of the Markov Chain Monte Carlo (MCMC) method to estimate the epidemiological parameters of infectious rate, fatality rate, recovery rate, and reproduction numbers. …”
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  9. 9
    Detection of multiple outliners in linear regression using nonparametric methods

    Detection of multiple outliners in linear regression using nonparametric methods by Adnan, Robiah

    Published 2004
    “…REFERENCES Agullo, J. (2000). New Algorithms for Computing the Least Trimmed Squares Regression Estimator. …”
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  10. 10
    Estimation of Information Measures for Power-Function Distribution in Presence of Outliers and Their Applications

    Estimation of Information Measures for Power-Function Distribution in Presence of Outliers and Their Applications by Hassan, Amal Soliman, Elsherpieny, Elsayed Ahmed, Mohamed, Rokaya Elmorsy

    Published 2022
    “…The Bayesian estimators were computed empirically using a Monte Carlo simulation based on the Gibbs sampling algorithm. …”
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  11. 11
    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. The Gibbs sampler algorithm is applied using the WinBUGS programming package. …”
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  12. 12
    Entropy in portfolio optimization / Yasaman Izadparast Shirazi

    Entropy in portfolio optimization / Yasaman Izadparast Shirazi by Yasaman Izadparast, Shirazi

    Published 2017
    “…The failure of this technique has been investigated and an adaptive beta-divergent method is proposed to ensure robust estimation. The usefulness of this technique has been verified with Monte-Carlo simulation in the context of portfolio analysis. …”
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  13. 13
    Visdom: Smart guide robot for visually impaired people

    Visdom: Smart guide robot for visually impaired people by Lee, Zhen Ting

    Published 2025
    “…The system architecture integrates ROS 2 on a Raspberry Pi, with TCP/IP connectivity enabling remote operation. An Android mobile application, developed using Java and the java.net.Socket library, provides an intuitive and accessible user interface for seamless interaction with the robot. …”
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  14. 14
    Satellite attitude determination utilizing measurement sensor data and kalman filtering

    Satellite attitude determination utilizing measurement sensor data and kalman filtering by Samaan, Malak A., Abdelrahman, Mohammad

    Published 2006
    “…This assessment was done by using Monte Carlo methods to simulate these sensors. Using only star measurements an optimal satellite orientation estimate is found using the method of least squares, and the particular algorithm invoked is referred to ESOQ2 method. …”
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  15. 15
    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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  16. 16
    Grouping based radio frequency identification anti-collision protocols for dense internet of things application

    Grouping based radio frequency identification anti-collision protocols for dense internet of things application by Umelo, Nnamdi H., Noordin, Nor K., A. Rasid, Mohd Fadlee, Geok, Tan K., Hashim, Fazirulhisyam

    Published 2022
    “…This paper analyzes selected grouping-based algorithms. Their underlining principles are discussed including their tag estimation methods. …”
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  17. 17
    A Bayesian parameter learning procedure for nonlinear dynamical systems via the ensemble Kalman filter

    A Bayesian parameter learning procedure for nonlinear dynamical systems via the ensemble Kalman filter by Ur Rehman, M.J., Dass, S.C., Asirvadam, V.S.

    Published 2018
    “…Based on observations made from stochastic dynamical systems, we consider the issue of parameter learning, and a related state estimation problem. We develop a Markov Chain Monte Carlo (MCMC) algorithm, which is an iterative method, for parameter inference. …”
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  18. 18
    Development Of Machine Learning User Interface For Pump Diagnostics

    Development Of Machine Learning User Interface For Pump Diagnostics by Lee, Zhao Yang

    Published 2022
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  19. 19
    Audio Streaming System Using Real-Time Transport Protocol Based on Java Media Framework

    Audio Streaming System Using Real-Time Transport Protocol Based on Java Media Framework by Asaad Aref, Ibrahim

    Published 2004
    “…A design proposal was outlined to provide an adaptive client/server approach to stream audio contents using Real-Time Transport Protocol (RTP) involving architecture based on the Java Media Framework (JMF) Application Programmable Interfaces (API).RTP protocol is the Internet-standard protocol for the transport of real-time data, including audio and video and can be implemented by using Java Media Framework (JMF). …”
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  20. 20
    Estimated and analysis of the relationship between the endogenous and exogenous variables using fuzzy semi-paranetric sample selection model

    Estimated and analysis of the relationship between the endogenous and exogenous variables using fuzzy semi-paranetric sample selection model by MuhamadSafiih, L, Kamil, A.A., Abu Osman, M.T.

    Published 2014
    “…The effectiveness of the estimators for this model is investigated. Monte Carlo simulation revealed that consistency depends on bandwidth parameter. …”
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