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Deanship of Graduate Studies
Document Details
Document Type
:
Thesis
Document Title
:
COMPARATIVE STUDY ABOUT EFRON S BOOTSTRAP METHOD AND SMOOTHED EFRON S BOOTSTRAP METHOD
دراسة مقارنة بين طريقة إفرون للبوتستراب والطريقة الممهدة لطريقة إفرون للبوتستراب
Subject
:
Faculty of Science
Document Language
:
Arabic
Abstract
:
The bootstrap method is a popular and useful technique in statistical research. It is an interesting topic for many studies, and can be used for all types of data and complex estimations. This thesis is a comparative study between two different types of bootstrap methods, Efron’s bootstrap method and the smoothed Efron’s bootstrap method. Efron’s bootstrap method involves resampling with replacement, while the smoothed Efron’s bootstrap method is depended on dividing data into intervals and selecting observations from them. The methods are compared in three different ways, with the use of estimation, prediction and histograms. This involved the estimation of standard error, the absolute value of bias, and the mean square error for mean, median, and variance. Predict the prediction interval with three different estimates and three different values for the coverage. Present a histogram of two bootstrap methods samples to compare between them and compare them with original sample by different measure. Evaluate the stability and the variability of the hypothesis test result by estimate the reproducibility probability. The smoothed Efron’s bootstrap method returns a better result at the prediction interval, and is more stable in terms of reproducibility probability with a small sample size than Efron’s bootstrap method. Meanwhile, in most cases Efron’s bootstrap method returns a better result in measures of accuracy, especially with a small sample size and symmetric distributions. Furthermore, it exhibits less skewness and dispersion in histogram graphs. The results are presented with the use of a simulation study.
Supervisor
:
Dr. Sulafah M. Saleh BinHimd
Thesis Type
:
Master Thesis
Publishing Year
:
1441 AH
2020 AD
Co-Supervisor
:
Dr. Zakia Ebrahim Kalantan
Added Date
:
Monday, June 15, 2020
Researchers
Researcher Name (Arabic)
Researcher Name (English)
Researcher Type
Dr Grade
Email
بشائر عبدالرحمن المالكي
Almalki, Bashair Abdulrahman
Researcher
Master
Files
File Name
Type
Description
46410.pdf
pdf
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