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  1. 1
    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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  2. 2
    Kalman filter based impedance parameter estimation for transmission line and distribution line

    Kalman filter based impedance parameter estimation for transmission line and distribution line by Siti Nur Aishah, Mohd Amin

    Published 2019
    “…Therefore, a detailed study on developing and evaluating the new algorithms for transmission line parameter estimation is considered in this thesis. …”
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  3. 3
    Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets

    Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets by Saeed, Sana

    Published 2019
    “…A new self-adaptive hybrid algorithm (CSCMAES) is introduced for optimization. …”
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  4. 4
    Prior selection for Gumbel distribution parameters using multiple-try metropolis algorithm for monthly maxima PM10 data

    Prior selection for Gumbel distribution parameters using multiple-try metropolis algorithm for monthly maxima PM10 data by Mohd Amin, Nor Azrita, Adam, Mohd Bakri, Ibrahim, Noor Akma

    Published 2013
    “…The Multiple-try Metropolis (MTM) algorithm is the new alternatives in the field of Bayesian extremes for summarizing the posterior distribution. …”
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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 propose a new and efficient approximation of the concentration parameter estimates using two approaches, namely, the roots of a polynomial function and minimizing the negative value of the loglikelihood function in this study. …”
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  6. 6
    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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  7. 7
    On a new transmuted three-parameter lindley distribution and its applications

    On a new transmuted three-parameter lindley distribution and its applications by Xi, Yuhang, Lu, Hezhi, Liang, Fei

    Published 2024
    “…In this paper, a new transmuted three-parameter Lindley distribution (TTHPLD) is established using the transmutation map method, which includes the Lindley distribution, two-parameter Lindley distribution, transmuted two-parameter Lindley distribution and three-parameter Lindley distribution as special cases. …”
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  8. 8
    Location determination using radio frequency RSSI and deterministic algorithm

    Location determination using radio frequency RSSI and deterministic algorithm by Hussin, A.G., Hassan, S.F., Zubairi, Y.Z., Zaharim, A., Sopian, K.

    Published 2008
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  9. 9
    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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  10. 10
    Adaptive policing and shaping algorithms on inbound traffic using generalized Pareto distribution / Nor Azura Ayop

    Adaptive policing and shaping algorithms on inbound traffic using generalized Pareto distribution / Nor Azura Ayop by Ayop, Nor Azura

    Published 2016
    “…Log likelihood estimation technique is used to fit the best 2-parameter CDF compared to Weibull, Normal and Rician distribution model. …”
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  11. 11
    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
    “…The presence of excess zeros is also closely related to over dispersion. Two new mixed Poisson distributions, namely a three-parameter Poisson-exponentiated Weibull distribution and a fourparameter generalized Sichel distribution is introduced to model over dispersed, zeroinflated and long-tailed count data. …”
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  12. 12
    Poisson Transmuted Exponential Distribution For Count Data With Skewed, Dispersed And Excess Zero

    Poisson Transmuted Exponential Distribution For Count Data With Skewed, Dispersed And Excess Zero by Ademola Abiodun, Adetunji

    Published 2024
    “…Different Moment-Based Mathematical Properties Of The New Proposed Distributions Are Obtained. Different Algorithms Are Used To Assess The Maximum Likelihood Estimates For The Parameters Of The Proposed Distributions.The Newton-Raphson And The Nelder-Mead, With Minimum Iterations For Convergence And Log-Likelihood Values, Provide Optimum Estimates. …”
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  13. 13
    Parameter estimation of Kumaraswamy Burr type X models based on cure models with or without covariates

    Parameter estimation of Kumaraswamy Burr type X models based on cure models with or without covariates by Yusuf, Madaki Umar

    Published 2017
    “…In this thesis, we considered two methods via the classical maximum likelihood estimation (MLE) and the Bayes estimation using the Gibbs sampling (G-S) algorithm to estimate the parameters of BKBX, KBX and Beta-Weibull (BWB) models. …”
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  14. 14
    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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  15. 15
    Multiple-try Metropolis Hastings for modeling extreme PM10 data

    Multiple-try Metropolis Hastings for modeling extreme PM10 data by Mohd Amin, Nor Azrita, Adam, Mohd Bakri, Ibrahim, Noor Akma

    Published 2013
    “…The parameters were estimated using the new Bayesian approach in extreme called Multiple Try Metropolis-Hastings algorithms. …”
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  16. 16
    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
    “…Comparison was made between the air pollution parameter and the results using different colour paper or wall of a building as a reference surface. …”
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  17. 17
    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 statistical and regression properties, parameter estimation, forecasting, and graphical analysis for the new model have been examined. …”
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  18. 18
    New learning algorithm based on Hidden Markov Model (HMM) as stochastic modelling for pattern calssification

    New learning algorithm based on Hidden Markov Model (HMM) as stochastic modelling for pattern calssification by Balakrishnan, Malarvili, Ting, Chee Ming, Shaikh Salleh, Sheikh Hussain

    Published 2009
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    Monograph
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  19. 19
    Predicting the popularity of tweets using the theory of point processes.

    Predicting the popularity of tweets using the theory of point processes. by Tan, Wai Hong

    Published 2019
    “…The mode of the posterior distribution is used as the estimator of the finite-dimensional parameter, and suitable functionals of the predictive distribution for the number of retweets implied by the estimated model are used to predict the tweet popularity. …”
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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
    “…Through the bandwidth parameter also reveals that the estimated parameter is efficient, i.e., the S.D, MSE and RMSE values become smaller as N increased. …”
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