Several new kernel estimators for population abundance

Baker Albadareen, Noriszura Ismail

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The parameter f(0) is crucial in line transect sampling which is regularly used for computing population abundance in wildlife. The usual kernel estimator of f(0) has a high negative bias. Our study proposes several new estimators which are shown to be more efficient than the usual kernel estimator. A simulation technique is adopted to compare the performance of the proposed estimators with the classical kernel estimator. An application of the new estimators on real data set is discussed.

Original languageEnglish
Title of host publication4th International Conference on Mathematical Sciences - Mathematical Sciences
Subtitle of host publicationChampioning the Way in a Problem Based and Data Driven Society, ICMS 2016
PublisherAmerican Institute of Physics Inc.
Volume1830
ISBN (Electronic)9780735414983
DOIs
Publication statusPublished - 27 Apr 2017
Event4th International Conference on Mathematical Sciences - Mathematical Sciences: Championing the Way in a Problem Based and Data Driven Society, ICMS 2016 - Putrajaya, Malaysia
Duration: 15 Nov 201617 Nov 2016

Other

Other4th International Conference on Mathematical Sciences - Mathematical Sciences: Championing the Way in a Problem Based and Data Driven Society, ICMS 2016
CountryMalaysia
CityPutrajaya
Period15/11/1617/11/16

Fingerprint

estimators
wildlife
sampling
simulation

ASJC Scopus subject areas

  • Physics and Astronomy(all)

Cite this

Albadareen, B., & Ismail, N. (2017). Several new kernel estimators for population abundance. In 4th International Conference on Mathematical Sciences - Mathematical Sciences: Championing the Way in a Problem Based and Data Driven Society, ICMS 2016 (Vol. 1830). [080018] American Institute of Physics Inc.. https://doi.org/10.1063/1.4981002

Several new kernel estimators for population abundance. / Albadareen, Baker; Ismail, Noriszura.

4th International Conference on Mathematical Sciences - Mathematical Sciences: Championing the Way in a Problem Based and Data Driven Society, ICMS 2016. Vol. 1830 American Institute of Physics Inc., 2017. 080018.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Albadareen, B & Ismail, N 2017, Several new kernel estimators for population abundance. in 4th International Conference on Mathematical Sciences - Mathematical Sciences: Championing the Way in a Problem Based and Data Driven Society, ICMS 2016. vol. 1830, 080018, American Institute of Physics Inc., 4th International Conference on Mathematical Sciences - Mathematical Sciences: Championing the Way in a Problem Based and Data Driven Society, ICMS 2016, Putrajaya, Malaysia, 15/11/16. https://doi.org/10.1063/1.4981002
Albadareen B, Ismail N. Several new kernel estimators for population abundance. In 4th International Conference on Mathematical Sciences - Mathematical Sciences: Championing the Way in a Problem Based and Data Driven Society, ICMS 2016. Vol. 1830. American Institute of Physics Inc. 2017. 080018 https://doi.org/10.1063/1.4981002
Albadareen, Baker ; Ismail, Noriszura. / Several new kernel estimators for population abundance. 4th International Conference on Mathematical Sciences - Mathematical Sciences: Championing the Way in a Problem Based and Data Driven Society, ICMS 2016. Vol. 1830 American Institute of Physics Inc., 2017.
@inproceedings{6876269066a4469d82b3ec34c7951140,
title = "Several new kernel estimators for population abundance",
abstract = "The parameter f(0) is crucial in line transect sampling which is regularly used for computing population abundance in wildlife. The usual kernel estimator of f(0) has a high negative bias. Our study proposes several new estimators which are shown to be more efficient than the usual kernel estimator. A simulation technique is adopted to compare the performance of the proposed estimators with the classical kernel estimator. An application of the new estimators on real data set is discussed.",
author = "Baker Albadareen and Noriszura Ismail",
year = "2017",
month = "4",
day = "27",
doi = "10.1063/1.4981002",
language = "English",
volume = "1830",
booktitle = "4th International Conference on Mathematical Sciences - Mathematical Sciences",
publisher = "American Institute of Physics Inc.",

}

TY - GEN

T1 - Several new kernel estimators for population abundance

AU - Albadareen, Baker

AU - Ismail, Noriszura

PY - 2017/4/27

Y1 - 2017/4/27

N2 - The parameter f(0) is crucial in line transect sampling which is regularly used for computing population abundance in wildlife. The usual kernel estimator of f(0) has a high negative bias. Our study proposes several new estimators which are shown to be more efficient than the usual kernel estimator. A simulation technique is adopted to compare the performance of the proposed estimators with the classical kernel estimator. An application of the new estimators on real data set is discussed.

AB - The parameter f(0) is crucial in line transect sampling which is regularly used for computing population abundance in wildlife. The usual kernel estimator of f(0) has a high negative bias. Our study proposes several new estimators which are shown to be more efficient than the usual kernel estimator. A simulation technique is adopted to compare the performance of the proposed estimators with the classical kernel estimator. An application of the new estimators on real data set is discussed.

UR - http://www.scopus.com/inward/record.url?scp=85019407309&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85019407309&partnerID=8YFLogxK

U2 - 10.1063/1.4981002

DO - 10.1063/1.4981002

M3 - Conference contribution

AN - SCOPUS:85019407309

VL - 1830

BT - 4th International Conference on Mathematical Sciences - Mathematical Sciences

PB - American Institute of Physics Inc.

ER -