Browsing by Author "Nurul Hila Zainuddin"

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    Pemodelan gerakan garisan tengah purata bergerak berpemberat secara eksponen dengan pendekatan cangkuk but (Bootstrap)
    (Terengganu: Universiti Malaysia Terengganu, 2013-09-23) Nurul Hila Zainuddin
    Sukuk Musyarakah adalah satu instrumen pelaburan bon Islam di Malaysia yang berasaskan penstrukturan semula bon konvensional menjadi bon patuh Syariah. Sebagaimana bon konvensional, kemruapan bon sukuk Musyarakah memainkan peranan penting dalam bidang pelaburan. Pulangan pelaburan sukuk adalah merupakan data siri masa yang bersifat bersandar dan berkolerasi semulajadi. Dalam proses kawalan berstatistik (Statistical Process Control, SPC), model carta piawai Purata Bergerak Berpemberat Secara Eksponen (Exponentially Weighted Moving Average, EWMA) banyak diaplikasikan dalam bidang kewangan, namun begitu carta ini digunakan untuk mengawas taburan data yang bersifat tidak bersandar dan sepercaman (independent and indentically distribution, iid).
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    The Performance of Double Bootstrap Method for Large Sampling Sequence
    (Open Journal of Statistics, 2016-10) Muhamad Safiih Lola; Nurul Hila Zainuddin
    Studies on the iteration procedure in double bootstrap method have given a great impact on confidence interval performance. However, the procedure was claimed to be complicated and demand intensive computer processor. Considering this problem, an alternative procedure was proposed in this research. Despite of using small sampling sequence, this research was aimed to increase the accuracy estimation using a second replication number which resulted in a large sampling sequence of double bootstrap. In this paper, the alternative double bootstrap method was hybrid onto an example model and its performance was based on Studentised interval. The performance was examined in simulation study and real sample data of sukuk Ijarah. The result showed that hybrid double bootstrap model gave more accurate estimation in terms of its shorter length when dealing with various parameter values and has shown to improve the single bootstrap estimation.
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    Sample Selection Model with Bootstrap (BPSSM) Approach:
    (Scientific Research Publishing, 2016) Muhamad Safiih Lola; Wan Saliha Wan Alwi; Nurul Hila Zainuddin
    Heckman Sampel Selection Model (PSSM) has been adopted widely in the study of labour work. This model contains exogenous, endogenous and standard error variables. However, this model is constantly exposed to high inaccuracy of estimation result. Therefore, to obtain an accurate and precise estimation, the bootstrap approach is introduced. The bootstrap approach will be hybrid with PSSM model known as BPSSM to achieve estimation result that is more precise. Then, the BPSSM is applied to Malaysian Population and Family Survey 1994 (MPFS-1994) data. The results showed that BPSSM provide a smaller standard error and shorter confidence intervals.