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Comparison of Ordinary Least Square and Mixed-Effect Regression Models for Estimation of Tree Diameter Increment: A Case Study for Dipterocarpacea in Siem Reap, Cambodia

Diameter increment is one of the common and important tree characteristics used in forest management decision making. In this paper, we compared different statistical methods to develop diameter increment models for individual tree of dipterocarpaceae tree species in semi-evergreen forest in Seam Re...

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Main Authors: Suriyati Harun, Yasmin Yahya, Nurashikin Saaludin, Wan Suriyani Che Wan Ahmad, (UniKL MIIT)
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Published: ACM 2015
Subjects:
Ordinary least square model
mixed effect model
repeated measures
model validation
Online Access:http://localhost/xmlui/handle/123456789/9719
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record_format eprints
spelling my.unikl.ir-97192015-03-30T03:25:20Z Comparison of Ordinary Least Square and Mixed-Effect Regression Models for Estimation of Tree Diameter Increment: A Case Study for Dipterocarpacea in Siem Reap, Cambodia Suriyati Harun Yasmin Yahya Nurashikin Saaludin Wan Suriyani Che Wan Ahmad (UniKL MIIT) Ordinary least square model mixed effect model repeated measures model validation Diameter increment is one of the common and important tree characteristics used in forest management decision making. In this paper, we compared different statistical methods to develop diameter increment models for individual tree of dipterocarpaceae tree species in semi-evergreen forest in Seam Reap, Cambodia. The two chosen methods were ordinary least square (OLS) and linear mixed effect model (LME) techniques. The aim was to clarify the effect of taking into account the repeated measurement of the data. Instead of the predicted parameters, we focused on the performance between the methods. The models were validated in terms of mean square error and mean percent error using independent test data set. The result showed mixed effect model was superior as it produced smaller prediction error. 2015-03-30T03:25:20Z 2015-03-30T03:25:20Z 2015-01 BibTeX | EndNote | ACM Ref Suriyati Harun, Yasmin Yahya, Nurashikin Saaludin, and Wan Suriyani Che Wan Ahmad. 2015. Comparison of ordinary least square and mixed-effect regression models for estimation of tree diameter increment: a case study for dipterocarpacea in Siem Reap, Cambodia. In Proceedings of the 9th International Conference on Ubiquitous Information Management and Communication (IMCOM '15). ACM, New York, NY, USA, , Article 85 , 6 pages. DOI=10.1145/2701126.2701167 http://doi.acm.org/10.1145/2701126.270116 978-1-4503-3377-1 http://localhost/xmlui/handle/123456789/9719 ACM
institution Universiti Kuala Lumpur
building UniKL Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Kuala Lumpur
content_source UniKL Institutional Repository
url_provider http://ir.unikl.edu.my/
topic Ordinary least square model
mixed effect model
repeated measures
model validation
spellingShingle Ordinary least square model
mixed effect model
repeated measures
model validation
Suriyati Harun
Yasmin Yahya
Nurashikin Saaludin
Wan Suriyani Che Wan Ahmad
(UniKL MIIT)
Comparison of Ordinary Least Square and Mixed-Effect Regression Models for Estimation of Tree Diameter Increment: A Case Study for Dipterocarpacea in Siem Reap, Cambodia
description Diameter increment is one of the common and important tree characteristics used in forest management decision making. In this paper, we compared different statistical methods to develop diameter increment models for individual tree of dipterocarpaceae tree species in semi-evergreen forest in Seam Reap, Cambodia. The two chosen methods were ordinary least square (OLS) and linear mixed effect model (LME) techniques. The aim was to clarify the effect of taking into account the repeated measurement of the data. Instead of the predicted parameters, we focused on the performance between the methods. The models were validated in terms of mean square error and mean percent error using independent test data set. The result showed mixed effect model was superior as it produced smaller prediction error.
format
author Suriyati Harun
Yasmin Yahya
Nurashikin Saaludin
Wan Suriyani Che Wan Ahmad
(UniKL MIIT)
author_facet Suriyati Harun
Yasmin Yahya
Nurashikin Saaludin
Wan Suriyani Che Wan Ahmad
(UniKL MIIT)
author_sort Suriyati Harun
title Comparison of Ordinary Least Square and Mixed-Effect Regression Models for Estimation of Tree Diameter Increment: A Case Study for Dipterocarpacea in Siem Reap, Cambodia
title_short Comparison of Ordinary Least Square and Mixed-Effect Regression Models for Estimation of Tree Diameter Increment: A Case Study for Dipterocarpacea in Siem Reap, Cambodia
title_full Comparison of Ordinary Least Square and Mixed-Effect Regression Models for Estimation of Tree Diameter Increment: A Case Study for Dipterocarpacea in Siem Reap, Cambodia
title_fullStr Comparison of Ordinary Least Square and Mixed-Effect Regression Models for Estimation of Tree Diameter Increment: A Case Study for Dipterocarpacea in Siem Reap, Cambodia
title_full_unstemmed Comparison of Ordinary Least Square and Mixed-Effect Regression Models for Estimation of Tree Diameter Increment: A Case Study for Dipterocarpacea in Siem Reap, Cambodia
title_sort comparison of ordinary least square and mixed-effect regression models for estimation of tree diameter increment: a case study for dipterocarpacea in siem reap, cambodia
publisher ACM
publishDate 2015
url http://localhost/xmlui/handle/123456789/9719
_version_ 1644485129074114560
score 13.222552

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