Articles | Volume 11, issue 2
https://doi.org/10.5194/amt-11-1233-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-11-1233-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Evaluation of linear regression techniques for atmospheric applications: the importance of appropriate weighting
Institute of Mass Spectrometer and Atmospheric Environment, Jinan
University, Guangzhou 510632, China
Guangdong Provincial Engineering Research Center for On-Line Source
Apportionment System of Air Pollution, Guangzhou 510632, China
Division of Environment, Hong Kong University of Science and
Technology, Clear Water Bay, Hong Kong, China
Atmospheric Research Centre, Fok Ying Tung Graduate School, Hong Kong
University of Science and Technology, Nansha, China
Department of Chemistry, Hong Kong University of Science and
Technology, Clear Water Bay, Hong Kong, China
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Latest update: 23 Nov 2024
Short summary
A new data generation scheme that employs the Mersenne twister (MT) pseudorandom number generator is proposed to conduct benchmark tests on a variety of linear regression techniques. With an appropriate weighting, Deming regression (DR), weighted ODR (WODR), and York regression (YR) are recommended for atmospheric studies when both x and y data have measurement errors. An Igor-based program (Scatter Plot) is developed to facilitate the regression implementation.
A new data generation scheme that employs the Mersenne twister (MT) pseudorandom number...