Kernel Estimation in Line Transect Sampling for Parametric Model

• Main Authors: Saeed, Gamil Abdulraqeb Abdullah, Noryanti, Muhammad, Wan Nur Syahidah, Wan Yusoff
• Format: Article
• Language: English
• Published: Akademi Sains Malaysia 2019
• Subjects: Q Science (General); T Technology (General)
• Online Access: http://umpir.ump.edu.my/id/eprint/25684/13/Kernel%20Estimation%20in%20Line%20Transect.pdf; http://umpir.ump.edu.my/id/eprint/25684/; https://www.akademisainhttps://www.akademisains.gov.my/asmsj/asm-sc-j-vol-12-special-issue-5-2019-for-icoaims2019/
• Institution: Universiti Malaysia Pahang

Line transect sampling is a common method used in ecology to sampling the sample required. It is an important procedure for estimating the population density of objects in interested study area. There are mainly two ways to estimate the population density which a parametric and nonparametric estimation methods. In this paper, we present kernel estimation method to estimate new estimator of the propose population density. Kernel estimation method is used due to avoid the assumption about the shape of the unknown detectable functions. We investigate the performance of the new estimator using simulation study and compared with the existing estimators. Based on the simulation study, the results show that the proposed estimator preforms better than other well-known estimators