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  1. 1
    Semiparametric estimation with profile algorithm for longitudinal binary data

    Semiparametric estimation with profile algorithm for longitudinal binary data by Suliadi, Suliadi, Ibrahim, Noor Akma, Daud, Isa

    Published 2013
    “…We use profile algorithm in the estimation of both parametric and nonparametric components. …”
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  2. 2
    Power prediction using the wind turbine power curve and data-driven approaches / Ehsan Taslimi Renani

    Power prediction using the wind turbine power curve and data-driven approaches / Ehsan Taslimi Renani by Ehsan Taslimi , Renani

    Published 2018
    “…Secondly, a new formula representing frequency distribution of the turbine power is derived. …”
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  3. 3
    GEE-smoothing spline in semiparametric model with correlated nominal data

    GEE-smoothing spline in semiparametric model with correlated nominal data by Ibrahim, Noor Akma, Suliadi

    Published 2010
    “…We use profile algorithm in the estimation of both parametric and nonparametric components. …”
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  4. 4
    Semiparametric binary model for clustered survival data

    Semiparametric binary model for clustered survival data by Arlin, Rifina, Ibrahim, Noor Akma, Arasan, Jayanthi, Abu Bakar, Mohd Rizam

    Published 2014
    “…A backfitting algorithm is used in the derivation of the estimating equation for the parametric and nonparametric components of a semiparametric binary covariate model. …”
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  5. 5
    Non-parametric maximum likelihood estimation of cure fraction for interval survival data.

    Non-parametric maximum likelihood estimation of cure fraction for interval survival data. by I. Aljawadi, Bader Ahmad, Abu Bakar, Mohd Rizam, Ibrahim, Noor Akma

    Published 2011
    “…We implement the Turnbull algorithm for the survival function estimation using EM algorithm. …”
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  6. 6
    Adaptive Similarity Component Analysis in Nonparametric Dynamic Environment

    Adaptive Similarity Component Analysis in Nonparametric Dynamic Environment by Sojodishijani, Omid

    Published 2011
    “…For this purpose, the most probable location of incoming instance for each class is estimated. Then, an optimal transformation matrix is computed by maximizing the information gain at the estimated points. …”
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  7. 7
    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
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  8. 8
    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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  9. 9
    Missing value estimation methods for data in linear functional relationship model

    Missing value estimation methods for data in linear functional relationship model by Adilah Abdul Ghapor, Yong Zulina Zubairi, A.H.M. Rahmatullah Imon

    Published 2017
    “…In this paper, two modern imputing approaches namely expectation-maximization (EM) and expectation-maximization with bootstrapping (EMB) are proposed in this paper for two kinds of linear functional relationship (LFRM) models, namely LFRM1 for full model and LFRM2 for linear functional relationship model when slope parameter is estimated using a nonparametric approach. The performance of EM and EMB are measured using mean absolute error, root-mean-square error and estimated bias. …”
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  10. 10
    Self-Schedule and Self-Distributive MAC Scheduling Algorithms for Next-Generation Sensor Networks

    Self-Schedule and Self-Distributive MAC Scheduling Algorithms for Next-Generation Sensor Networks by Bakhsh, S.T., Aman Sheikh, M., Alghamdi, R.

    Published 2015
    “…According to the proposed algorithms, each node maps a conflict-free time slot for itself up to 2-hop neighboring nodes. …”
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  11. 11
    An Improved Distributed Scheduling Algorithm for Wireless Sensor Networks

    An Improved Distributed Scheduling Algorithm for Wireless Sensor Networks by Sheikh, Muhammad Aman, Drieberg , Micheal, Zain Ali, Noohul Basheer

    Published 2012
    “…Simulation results show that the IDSA significantly outperforms a representative distributed random slot assignment algorithm (DRAND).…”
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  12. 12
    Support vector machine and its applications for linear and nonlinear regression in the presence of outliers of high dimensional data

    Support vector machine and its applications for linear and nonlinear regression in the presence of outliers of high dimensional data by Sleabi, Waleed Dhhan

    Published 2016
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  13. 13
    Distance vector-hop range-free location algorithm for wireless sensor network

    Distance vector-hop range-free location algorithm for wireless sensor network by Zazali, Azyyati Adiah

    Published 2015
    “…Distance Vector-Hop (DV-Hop) algorithm has become the focus of studies for range-free localization algorithms. …”
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  14. 14
    Non-Parametric and Parametric Estimations of Cure Fraction Using Right-and Interval-Censored Data

    Non-Parametric and Parametric Estimations of Cure Fraction Using Right-and Interval-Censored Data by Aljawdi, Bader

    Published 2011
    “…Then, a series of simulation studies was conducted to evaluate the performance of the proposed estimation approaches. This research investigated the non-parametric maximum likelihood estimation method for cure rate estimation by considering two common estimators for the survival function: 1) The Kaplan Meier (KM) estimator, which is suitable for the right censoring case; and 2) The Turnbull Estimator, which is suitable for the interval type of data censoring. …”
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  15. 15
    System Identification of XY Table ballscrew drive using parametric and non parametric frequency domain estimation via deterministic approach

    System Identification of XY Table ballscrew drive using parametric and non parametric frequency domain estimation via deterministic approach by Abdullah, Lokman, Jamaludin, Zamberi, Tsung Heng, Chiew, RAFAN, NUR AIDAWATY, syed mohamed, muhammad syafiq

    Published 2012
    “…Both parametric and nonparametric procedure. In addition, comparison of estimated model transfer function obtained via non-linear least square (NLLS) and Linear least square estimator algorithm were also being addressed. …”
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  16. 16
    Distributive and self-sustainable scheduling algorithm for wireless sensor networks

    Distributive and self-sustainable scheduling algorithm for wireless sensor networks by Sheikh, M.A., Ali, N.B.Z., Awang, A.

    Published 2013
    “…In this paper, we propose a distributive and self-sustainable scheduling algorithm (DSSA). …”
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  17. 17
    Distributive and self-sustainable scheduling algorithm for wireless sensor networks

    Distributive and self-sustainable scheduling algorithm for wireless sensor networks by Sheikh, M.A., Ali, N.B.Z., Awang, A.

    Published 2013
    “…In this paper, we propose a distributive and self-sustainable scheduling algorithm (DSSA). …”
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  18. 18
    Distributive and self-sustainable scheduling algorithm for wireless sensor networks

    Distributive and self-sustainable scheduling algorithm for wireless sensor networks by Sheikh, M.A., Ali, N.B.Z., Awang, A.

    Published 2013
    “…In this paper, we propose a distributive and self-sustainable scheduling algorithm (DSSA). …”
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  19. 19
    Non-regularized reconstruction of magnetic moment distribution of magnetic nanoparticles using barnacles mating optimizer

    Non-regularized reconstruction of magnetic moment distribution of magnetic nanoparticles using barnacles mating optimizer by Mohd Mawardi, Saari, Mohd Herwan, Sulaiman, Nurul Akmal, Che Lah, Mohd Razali, Daud, Kiwa, Toshihiko

    Published 2023
    “…A simulated magnetization curve of unimodal moment distributions from 1 mT to 1 T is used to minimize a model-free magnetic moment distribution. …”
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  20. 20
    Evaluation of Different Horizon Lengths in Single-agent Finite Impulse Response Optimizer

    Evaluation of Different Horizon Lengths in Single-agent Finite Impulse Response Optimizer by Tasiransurini, Ab Rahman, Mohd Ibrahim, Shapiai, Zuwairie, Ibrahim, Nor Hidayati, Abdul Aziz, Nor Azlina, Ab. Aziz, Mohd Saberi, Mohamad

    Published 2019
    “…In a real UFIR filter, the horizon length, N plays an important role to obtain the optimal estimation. In SAFIRO, N represents the repetition number of estimation part that needs to be done in finding an optimal solution. …”
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