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  1. 1

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

    Published 2018
    “…The hierarchical Bayesian approach is used to estimate the order and coefficients of the autoregressive model. …”
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  2. 2

    Simulation algorithm of bayesian approach for choice-conjoint model by Zulhanif

    Published 2011
    “…Therefore this research propose simulation algorithm of Bayesian approach for estimating parameter in MPM by Bayesian analysis to avoid computational difficulties in computing the maximum likelihood estimates (MLE).…”
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    Thesis
  3. 3

    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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  4. 4

    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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    Thesis
  5. 5

    Bayesian survival and hazard estimates for Weibull regression with censored data using modified Jeffreys prior by Ahmed, Al Omari Mohammed

    Published 2013
    “…Mean squared error (MSE) and absolute bias are obtained and used to compare the Bayesian and the maximum likelihood estimation through simulation studies. …”
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    Thesis
  6. 6

    Bayesian logistic regression model on risk factors of type 2 diabetes mellitus by Chiaka, Emenyonu Sandra

    Published 2016
    “…The Bayesian logistic regression methods made use of the metropolis hasting (Random walk algorithm) and the Gibbs sampler with the incorporation of non-informative flat prior and non-informative non-flat prior distributions to obtain the posterior distribution for each coefficient of the variables. …”
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    Thesis
  7. 7

    Dynamic Bayesian Networks and Variable Length Genetic Algorithm for Dialogue Act Recognition by Ali Yahya, Anwar

    Published 2007
    “…The results are compared with the results of static Bayesian networks and naïve bayes. The results confirm the merits of using dynamic Bayesian networks for dialogue act recognition. …”
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    Thesis
  8. 8

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

    Published 2013
    “…In this paper, a simulation study of Bayesian extreme values by using Markov Chain Monte Carlo via slice sampling algorithm is implemented. …”
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    Conference or Workshop Item
  9. 9

    Adaptive framed pseudo-Bayesian Aloha algorithm with priorities by Habaebi, Mohamed Hadi, Mohd Ali, Borhanuddin

    Published 2000
    “…A new wireless framed pseudo-bayesian Aloha algorithm with adaptive priorities, for wireless ATM reservation-based TDMA MAC prolocols, is presented. …”
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  10. 10

    Bayesian Network of Traffic Accidents in Malaysia by Zamzuri, Zamira Hasanah, Shabadin, Akmalia, Ishak, Siti Zaharah

    Published 2019
    “…By using Hill Climb (HC) and Tabu algorithms, the structure of the data was learnt and their relationship is estimated through the conditional probability based on the Bayes theorem. …”
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    Article
  11. 11

    Color Image Segmentation Based on Bayesian Theorem for Mobile Robot Navigation by Rahimizadeh, Hamid

    Published 2009
    “…In this study a decision boundary equation, which is acquired from class conditional probability density function (PDF) of colors, based on Bayes decision theory has been used for desired color segmentation. The estimation of unknown PDF is a common problem and in this study Gaussian kernel function which is most widely used nonparametric density estimation method has been used for PDF calculation. …”
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    Thesis
  12. 12

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

    Published 2006
    “…The Gibbs sampler algorithm is applied using the WinBUGS programming package. …”
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    Thesis
  13. 13

    Model of Bayesian tangent eye shape for eye capture by Nsaef, Asama Kuder, Jaafar, Azizah, Sliman, Layth, Sulaiman, Riza, O. K. Rahmat, Rahmita Wirza

    Published 2014
    “…Obtaining a method in extracting quality of eye images automatically from the video stream is the main area of interest in this study. Besides, a Bayesian inference solution called Bayesian Tangent Eye Shape Model (BTESM) was suggested depending on estimation of tangent shape. …”
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  14. 14

    A case study on quality of sleep and health using Bayesian networks by Hong , Choon Ong, Chiew , Seng Lee, Chye , Ching Sia

    Published 2012
    “…The network scores computation is implemented to estimate the fitting of the resulting network of each structural learning algorithm in order to choose the best-fitted network. …”
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    Variational Bayesian inference for exponentiated Weibull right censored survival data by Jibril Abubakar, Jibril Abubakar, Mohd Asrul Affendi Abdullah, Mohd Asrul Affendi Abdullah, Oyebayo Ridwan Olaniran, Oyebayo Ridwan Olaniran

    Published 2023
    “…The results from the experiments reveal that the Variational Bayesian (VB) approach is better than the competing Metropolis-Hasting Algorithm and the reference maximum likelihood estimates.…”
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  18. 18

    Artificial intelligence modelling approach for the prediction of CO-rich hydrogen production rate from methane dry reforming by Ayodele B.V., Mustapa S.I., Alsaffar M.A., Cheng C.K.

    Published 2023
    “…The best prediction was, however, obtained using the Bayesian regularization algorithm with the lowest standard error of estimates (SEE). …”
    Article
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    Artificial intelligence modelling approach for the prediction of CO-rich hydrogen production rate from methane dry reforming by Ayodele, Bamidele V., Siti Indati, Mustapa, Alsaffar, May Ali, Cheng, C. K.

    Published 2019
    “…The best prediction was, however, obtained using the Bayesian regularization algorithm with the lowest standard error of estimates (SEE). …”
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    Article