A parameter estimation program for the error-in-variable model
A parameter estimation method called the two-stage error-in-variable model was introduced to the models that have both dependent and independent variables subject to random errors. Even though an example was once provided to demonstrate how to use the model in a step-by-step fashion, it appears the...
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Published in | Ecological modelling Vol. 156; no. 2; pp. 225 - 236 |
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Main Authors | , |
Format | Journal Article |
Language | English |
Published |
Amsterdam
Elsevier B.V
01.11.2002
Elsevier |
Subjects | |
Online Access | Get full text |
ISSN | 0304-3800 1872-7026 |
DOI | 10.1016/S0304-3800(02)00173-4 |
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Abstract | A parameter estimation method called the two-stage error-in-variable model was introduced to the models that have both dependent and independent variables subject to random errors. Even though an example was once provided to demonstrate how to use the model in a step-by-step fashion, it appears the model would not be widely applicable without the support of computer programs that can be run on either a
pc or
unix platform. In this study, the programming codes written in the
matlab language are presented for the two-stage error-in-variable model; four estimation problems are solved with the program. It is hoped that the codes would make the method easy to use in systems ecology studies or any research involving estimation problems in which some variables are subject to errors while others have no random errors. |
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AbstractList | A parameter estimation method called the two-stage error-in-variable model was introduced to the models that have both dependent and independent variables subject to random errors. Even though an example was once provided to demonstrate how to use the model in a step-by-step fashion, it appears the model would not be widely applicable without the support of computer programs that can be run on either a
pc or
unix platform. In this study, the programming codes written in the
matlab language are presented for the two-stage error-in-variable model; four estimation problems are solved with the program. It is hoped that the codes would make the method easy to use in systems ecology studies or any research involving estimation problems in which some variables are subject to errors while others have no random errors. A parameter estimation method called the two-stage error-in-variable model was introduced to the models that have both dependent and independent variables subject to random errors. Even though an example was once provided to demonstrate how to use the model in a step-by-step fashion, it appears the model would not be widely applicable without the support of computer programs that can be run on either a PC or UNIX platform. In this study, the programming codes written in the MATLAB language are presented for the two-stage error-in-variable model; four estimation problems are solved with the program. It is hoped that the codes would make the method easy to use in systems ecology studies or any research involving estimation problems in which some variables are subject to errors while others have no random errors. |
Author | Tang, Shouzheng Wang, Yonghe |
Author_xml | – sequence: 1 givenname: Shouzheng surname: Tang fullname: Tang, Shouzheng email: stang@mail.forestry.ac.cn organization: The Institute of Forest Information Research, The Academy of Forestry of China, Beijing 100091, People's Republic of China – sequence: 2 givenname: Yonghe surname: Wang fullname: Wang, Yonghe email: ywang@nrcan.gc.ca organization: Department of Natural Resources of Canada, Northern Forestry Center, Canadian Forest Service, 5320-122 Street, Edmonton, Alta., Canada T6H 3S5 |
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SubjectTerms | Animal, plant and microbial ecology Biological and medical sciences Fundamental and applied biological sciences. Psychology General aspects. Techniques matlab programming language Methods and techniques (sampling, tagging, trapping, modelling...) Model I regression Model II regression Simultaneous equations Two-stage error-in-variable model |
Title | A parameter estimation program for the error-in-variable model |
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