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:	Conference or Workshop Item
Language:	English English
Published:	2018
Subjects:	QA Mathematics
Online Access:	http://umpir.ump.edu.my/id/eprint/24104/ http://umpir.ump.edu.my/id/eprint/24104/1/46.%20Performance%20of%20parametric%20model%20for%20line%20transect%20data.pdf http://umpir.ump.edu.my/id/eprint/24104/2/46.1%20Performance%20of%20parametric%20model%20for%20line%20transect%20data.pdf

id	ump-24104
recordtype	eprints
spelling	ump-241042019-02-13T07:39:38Z 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. 2018 Conference or Workshop Item NonPeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/24104/1/46.%20Performance%20of%20parametric%20model%20for%20line%20transect%20data.pdf pdf en http://umpir.ump.edu.my/id/eprint/24104/2/46.1%20Performance%20of%20parametric%20model%20for%20line%20transect%20data.pdf Saeed, Gamil Abdulraqeb Abdullah and Noryanti, Muhammad and Wan Nur Syahidah, Wan Yusoff (2018) Performance of parametric model for line transect data. In: Simposium Kebangsaan Sains Matematik Ke 26 (SKSM26) 2018, 28 - 29 November 2018 , Universiti Malaysia Sabah, Kota Kinabalu Sabah. pp. 1-9.. (Unpublished)
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Malaysia Pahang
building	UMP Institutional Repository
collection	Online Access
language	English 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	Conference or Workshop Item
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
publishDate	2018
url	http://umpir.ump.edu.my/id/eprint/24104/ http://umpir.ump.edu.my/id/eprint/24104/1/46.%20Performance%20of%20parametric%20model%20for%20line%20transect%20data.pdf http://umpir.ump.edu.my/id/eprint/24104/2/46.1%20Performance%20of%20parametric%20model%20for%20line%20transect%20data.pdf
first_indexed	2023-09-18T22:36:18Z
last_indexed	2023-09-18T22:36:18Z
_version_	1777416618699128832

Performance of parametric model for line transect data

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