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Performance of parametric model for line transect data

One of the most important sides of life is wildlife. There is growing research interest in monitoring wildlife. Line transect sampling is one of the techniques widely used for estimating the density of objects especially for animals and plants. In this study, we have developed a parametric estimator...

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Main Authors: Saeed, Gamil Abdulraqeb Abdullah, Noryanti, Muhammad, Wan Nur Syahidah, Wan Yusoff
Format: Article
Language:English
Published: Akademi Sains Malaysia 2020
Subjects:
QA Mathematics
Online Access:http://umpir.ump.edu.my/id/eprint/24104/13/Performance%20of%20parametric%20model%20for%20line%20transect%20data.pdf
http://umpir.ump.edu.my/id/eprint/24104/
https://doi.org/10.32802/asmscj.2020.sm26(1.18)
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spelling my.ump.umpir.241042020-10-12T07:52:32Z http://umpir.ump.edu.my/id/eprint/24104/ Performance of parametric model for line transect data Saeed, Gamil Abdulraqeb Abdullah Noryanti, Muhammad Wan Nur Syahidah, Wan Yusoff QA Mathematics One of the most important sides of life is wildlife. There is growing research interest in monitoring wildlife. Line transect sampling is one of the techniques widely used for estimating the density of objects especially for animals and plants. In this study, we have developed a parametric estimator f (0 ) for estimation of the population abundance. A new parametric model for perpendicular distances for detection function g ( z ) is utilized to develop the estimator f (0 ) . Moreover, we present the performance of the parametric model which was developed using simulation study. The detection function has nonincreasing curve and a perfect probability at zero. Theoretically, the parametric model that has been developed is guaranteed to satisfy the shoulder condition assumption. A simulation study is presented to validate the present model. Relative mean error (RME) is used to compare the estimator with well-known existing estimators. The results of the simulation study are discussed and the performance of the proposed model showed good statistical properties which out-performed the existing models. Akademi Sains Malaysia 2020 Article PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/24104/13/Performance%20of%20parametric%20model%20for%20line%20transect%20data.pdf Saeed, Gamil Abdulraqeb Abdullah and Noryanti, Muhammad and Wan Nur Syahidah, Wan Yusoff (2020) Performance of parametric model for line transect data. ASM Science Journal, 13 (Special 4). pp. 1-7. ISSN 1823-6782 https://doi.org/10.32802/asmscj.2020.sm26(1.18)
institution Universiti Malaysia Pahang
building UMP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Pahang
content_source UMP Institutional Repository
url_provider http://umpir.ump.edu.my/
language English
topic QA Mathematics
spellingShingle QA Mathematics
Saeed, Gamil Abdulraqeb Abdullah
Noryanti, Muhammad
Wan Nur Syahidah, Wan Yusoff
Performance of parametric model for line transect data
description One of the most important sides of life is wildlife. There is growing research interest in monitoring wildlife. Line transect sampling is one of the techniques widely used for estimating the density of objects especially for animals and plants. In this study, we have developed a parametric estimator f (0 ) for estimation of the population abundance. A new parametric model for perpendicular distances for detection function g ( z ) is utilized to develop the estimator f (0 ) . Moreover, we present the performance of the parametric model which was developed using simulation study. The detection function has nonincreasing curve and a perfect probability at zero. Theoretically, the parametric model that has been developed is guaranteed to satisfy the shoulder condition assumption. A simulation study is presented to validate the present model. Relative mean error (RME) is used to compare the estimator with well-known existing estimators. The results of the simulation study are discussed and the performance of the proposed model showed good statistical properties which out-performed the existing models.
format Article
author Saeed, Gamil Abdulraqeb Abdullah
Noryanti, Muhammad
Wan Nur Syahidah, Wan Yusoff
author_facet Saeed, Gamil Abdulraqeb Abdullah
Noryanti, Muhammad
Wan Nur Syahidah, Wan Yusoff
author_sort Saeed, Gamil Abdulraqeb Abdullah
title Performance of parametric model for line transect data
title_short Performance of parametric model for line transect data
title_full Performance of parametric model for line transect data
title_fullStr Performance of parametric model for line transect data
title_full_unstemmed Performance of parametric model for line transect data
title_sort performance of parametric model for line transect data
publisher Akademi Sains Malaysia
publishDate 2020
url http://umpir.ump.edu.my/id/eprint/24104/13/Performance%20of%20parametric%20model%20for%20line%20transect%20data.pdf
http://umpir.ump.edu.my/id/eprint/24104/
https://doi.org/10.32802/asmscj.2020.sm26(1.18)
_version_ 1681489626830733312
score 13.211869

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