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  1. 1

    LASSO-type estimations for threshold autoregressive and heteroscedastic time series models. by Muhammad Jaffri Mohd Nasir

    Published 2020
    “…In this thesis, we propose Least Absolute Shrinkage and Selection Operator (LASSO) type estimators to perform simultaneous parameter estimation and model selection for five specific univariate and multivariate time series models, and develop several algorithms to compute these estimators. …”
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    UMK Etheses
  2. 2

    RSA Encryption & Decryption using JAVA by Ramli, Marliyana

    Published 2006
    “…References and theories to support the research of 'RSA Encryption/Decryption using Java' have been disclosed in Literature Review section. …”
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    Final Year Project
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    Machine Learning Regression Approach for Estimating Energy Consumption of Appliances in Smart Home by Husin N.S.I.M., Mostafa S.A., Jaber M.M., Gunasekaran S.S., Al-Shakarchi A.H., Abdulsattar N.F.

    Published 2024
    “…This paper attempts to use machine learning algorithms to estimate the energy consumption of appliances in a smart home environment. …”
    Conference Paper
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    Evaluation of a spacecraft attitude and rate estimation algorithm by Abdullah, Mohammad Nizam Filipski, Varatharajoo, Renuganth

    Published 2010
    “…Practical implications: Because the simulation set‐up is clearly stated, the results of this evaluation can be used as a benchmark for other estimation algorithms. …”
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    Article
  7. 7

    Unscented Kalman filter for noisy multivariate financial time-series data by Jadid Abdulkadir, S., Yong, S.-P.

    Published 2013
    “…In this paper, we consider the process of applying Unscented Kalman Filtering algorithm to multivariate financial time series data to determine if the algorithm could be used to smooth the direction of KLCI stock price movements using five different measurement variance values. …”
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    Article
  8. 8

    Unscented Kalman filter for noisy multivariate financial time-series data by Jadid Abdulkadir, S., Yong, S.-P.

    Published 2013
    “…In this paper, we consider the process of applying Unscented Kalman Filtering algorithm to multivariate financial time series data to determine if the algorithm could be used to smooth the direction of KLCI stock price movements using five different measurement variance values. …”
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    Article
  9. 9

    Unscented Kalman filter for noisy multivariate financial time-series data by Jadid Abdulkadir, S., Yong, S.-P.

    Published 2013
    “…In this paper, we consider the process of applying Unscented Kalman Filtering algorithm to multivariate financial time series data to determine if the algorithm could be used to smooth the direction of KLCI stock price movements using five different measurement variance values. …”
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    Article
  10. 10

    Unscented Kalman filter for noisy multivariate financial time-series data by Jadid Abdulkadir, S., Yong, S.-P.

    Published 2013
    “…In this paper, we consider the process of applying Unscented Kalman Filtering algorithm to multivariate financial time series data to determine if the algorithm could be used to smooth the direction of KLCI stock price movements using five different measurement variance values. …”
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    Article
  11. 11

    Unscented Kalman filter for noisy multivariate financial time-series data by Jadid Abdulkadir, S., Yong, S.-P.

    Published 2013
    “…In this paper, we consider the process of applying Unscented Kalman Filtering algorithm to multivariate financial time series data to determine if the algorithm could be used to smooth the direction of KLCI stock price movements using five different measurement variance values. …”
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    Article
  12. 12

    Properties of selected garma models and their estimation procedures by Ramiah Pillai, Thulasyammal

    Published 2012
    “…The focus of this study is to investigate the properties specically the variance and autocovariance of the GARMA (p; q; ±1; ±2) models. We also study the estimation of the parameters of these models. Evaluation of the performance of two estimators based on the Hannan-Rissanen Algorithm Estimator (HRA) and the Whittle's Estimator (WE) through a series of simulation studies have been conducted in this thesis. …”
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    Thesis
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    Parameter estimation in double exponential smoothing using genetic algorithm / Foo Fong Yeng, Lau Gee Choon and Zuhaimy Ismail by Foo, Fong Yeng, Lau, Gee Choon, Ismail, Zuhaimy

    Published 2014
    “…The objective of this research is to estimate the Double Exponential Smoothing by using Genetic Algorithm Mechanism. …”
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    Research Reports
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    Real-Time Video Processing Using Native Programming on Android Platform by Saipullah, Khairul Muzzammil

    Published 2012
    “…However for the Android platform that based on the JAVA language, most of the software algorithm is running on JAVA that consumes more time to be compiled. …”
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    Conference or Workshop Item
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    An investigation of structural breaks on spot and futures crude palm oil returns by Zainudin, Rozaimah, Shaharudin, Roselee Shah

    Published 2011
    “…Using the Inclan and Tioa Iterated Cumulative Sums of Squares (ICSS) algorithm procedures, we proceed to identify any structural changes in series variance. …”
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    Article
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    An Illustration of Generalised ARMA (GARMA) Time Series Modelling of Forest Area in Malaysia. by Pillai , Thulasyammal Ramiah, Shitan, Mahendran

    Published 2012
    “…The estimation of the model was done using Hannan-Rissanen Algorithm, Whittle's Estimation and Maximum Likelihood Estimation. …”
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    Article
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    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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    Thesis
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    Identifying homogeneous rainfall catchments for non-stationary time series using TOPSIS algorithm and bootstrap K-sample Anderson-Darling test by Chuan, Zun Liang, Noriszura, Ismail, Wan Nur Syahidah, Wan Yusoff, Soo-Fen, Fam, Mohd Akramin, Mohd Romlay

    Published 2018
    “…The Cophenetic Correlation Coefficients (CCC) from ten similarity measures are used as attributes for the TOPSIS algorithm to identify the most suitable AHC algorithm out of seven algorithms considered. …”
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    Article