A comparison of asymptotic and bootstrapping approach in constructing confidence interval of the concentration parameter in von mises distribution

Bootstrap is a resampling procedure for estimating the distributions of statistics based on independent observations. Basically, bootstrapping has been established for the use of parameter estimation of linear data. Thus, the used of bootstrap in confidence interval of the concentration parameter, κ...

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Main Authors: Nor Hafizah, Moslim, Yong Zulina, Zubairi, Abdul Ghapor, Hussin, Siti Fatimah, Hassan, Nurkhairany Amyra, Mokhtar
Format: Article
Language:English
Published: Universiti Kebangsaan Malaysia 2019
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/27585/
http://umpir.ump.edu.my/id/eprint/27585/1/A%20comparison%20of%20asymptotic%20and%20bootstrapping%20approach%20in%20constructing.pdf
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author Nor Hafizah, Moslim
Yong Zulina, Zubairi
Abdul Ghapor, Hussin
Siti Fatimah, Hassan
Nurkhairany Amyra, Mokhtar
author_facet Nor Hafizah, Moslim
Yong Zulina, Zubairi
Abdul Ghapor, Hussin
Siti Fatimah, Hassan
Nurkhairany Amyra, Mokhtar
author_sort Nor Hafizah, Moslim
building UMP Institutional Repository
collection Online Access
description Bootstrap is a resampling procedure for estimating the distributions of statistics based on independent observations. Basically, bootstrapping has been established for the use of parameter estimation of linear data. Thus, the used of bootstrap in confidence interval of the concentration parameter, κ in von Mises distribution which fitted the circular data is discussed in this paper. The von Mises distribution is the ’natural’ analogue on the circle of the Normal distribution on the real line and widely used to describe circular variables. The distribution has two parameters, namely mean direction, µ and concentration parameter, κ, respectively. The confidence interval based on the calibration bootstrap method will be compared with the existing method, confidence interval based on the asymptotic to the distribution of . Simulation studies were conducted to examine the empirical performance of the confidence intervals. Numerical results suggest the superiority of the proposed method based on measures of coverage probability and expected length. The confidence intervals were illustrated using daily wind direction data recorded at maximum wind speed for seven stations in Malaysia. From point estimates of the concentration parameter and the respective confidence interval, we note that the method works well for a wide range of κ values. This study suggests that the method of obtaining the confidence intervals can be applied with ease and provides good estimates.
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spelling ump-275852020-04-06T02:30:30Z http://umpir.ump.edu.my/id/eprint/27585/ A comparison of asymptotic and bootstrapping approach in constructing confidence interval of the concentration parameter in von mises distribution Nor Hafizah, Moslim Yong Zulina, Zubairi Abdul Ghapor, Hussin Siti Fatimah, Hassan Nurkhairany Amyra, Mokhtar QA Mathematics TA Engineering (General). Civil engineering (General) TK Electrical engineering. Electronics Nuclear engineering Bootstrap is a resampling procedure for estimating the distributions of statistics based on independent observations. Basically, bootstrapping has been established for the use of parameter estimation of linear data. Thus, the used of bootstrap in confidence interval of the concentration parameter, κ in von Mises distribution which fitted the circular data is discussed in this paper. The von Mises distribution is the ’natural’ analogue on the circle of the Normal distribution on the real line and widely used to describe circular variables. The distribution has two parameters, namely mean direction, µ and concentration parameter, κ, respectively. The confidence interval based on the calibration bootstrap method will be compared with the existing method, confidence interval based on the asymptotic to the distribution of . Simulation studies were conducted to examine the empirical performance of the confidence intervals. Numerical results suggest the superiority of the proposed method based on measures of coverage probability and expected length. The confidence intervals were illustrated using daily wind direction data recorded at maximum wind speed for seven stations in Malaysia. From point estimates of the concentration parameter and the respective confidence interval, we note that the method works well for a wide range of κ values. This study suggests that the method of obtaining the confidence intervals can be applied with ease and provides good estimates. Universiti Kebangsaan Malaysia 2019 Article PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/27585/1/A%20comparison%20of%20asymptotic%20and%20bootstrapping%20approach%20in%20constructing.pdf Nor Hafizah, Moslim and Yong Zulina, Zubairi and Abdul Ghapor, Hussin and Siti Fatimah, Hassan and Nurkhairany Amyra, Mokhtar (2019) A comparison of asymptotic and bootstrapping approach in constructing confidence interval of the concentration parameter in von mises distribution. Sains Malaysiana, 48 (5). pp. 1151-1156. ISSN 0126-6039. (Published) http://dx.doi.org/10.17576/jsm-2019-4805-24 http://dx.doi.org/10.17576/jsm-2019-4805-24
spellingShingle QA Mathematics
TA Engineering (General). Civil engineering (General)
TK Electrical engineering. Electronics Nuclear engineering
Nor Hafizah, Moslim
Yong Zulina, Zubairi
Abdul Ghapor, Hussin
Siti Fatimah, Hassan
Nurkhairany Amyra, Mokhtar
A comparison of asymptotic and bootstrapping approach in constructing confidence interval of the concentration parameter in von mises distribution
title A comparison of asymptotic and bootstrapping approach in constructing confidence interval of the concentration parameter in von mises distribution
title_full A comparison of asymptotic and bootstrapping approach in constructing confidence interval of the concentration parameter in von mises distribution
title_fullStr A comparison of asymptotic and bootstrapping approach in constructing confidence interval of the concentration parameter in von mises distribution
title_full_unstemmed A comparison of asymptotic and bootstrapping approach in constructing confidence interval of the concentration parameter in von mises distribution
title_short A comparison of asymptotic and bootstrapping approach in constructing confidence interval of the concentration parameter in von mises distribution
title_sort comparison of asymptotic and bootstrapping approach in constructing confidence interval of the concentration parameter in von mises distribution
topic QA Mathematics
TA Engineering (General). Civil engineering (General)
TK Electrical engineering. Electronics Nuclear engineering
url http://umpir.ump.edu.my/id/eprint/27585/
http://umpir.ump.edu.my/id/eprint/27585/
http://umpir.ump.edu.my/id/eprint/27585/
http://umpir.ump.edu.my/id/eprint/27585/1/A%20comparison%20of%20asymptotic%20and%20bootstrapping%20approach%20in%20constructing.pdf