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Improvement of Suspended Solid Loads Estimation in Nakdong River Using Minimum Variance Unbiased Estimator  

Han, Suhee (Department of Environmental System Engineering, Pukyong National University)
Kang, Du Kee (Department of Civil Engineering, Pusan National University)
Shin, Hyun Suk (Department of Civil Engineering, Pusan National University)
Yu, Jae-Jeong (Nakdong River Water Environmental Research Center, National Institute of Environmental Research)
Kim, Sangdan (Department of Environmental System Engineering, Pukyong National University)
Publication Information
Journal of Korean Society on Water Environment / v.23, no.2, 2007 , pp. 251-259 More about this Journal
Abstract
In this study three log-transformed linear regression models are compared with the focus of bias correction problem. The models are the traditional simple linear regression estimator (SL), the quasi maximum likelihood estimator (QMLE) and the minimum variance unbiased estimator (MVUE). Using such models, suspended solid loads can be estimated using the discharge - suspended solid data set that has been measured by NIER Nakdong River Water Environment Laboratory. As a result, SL shows negative bias for most values of the measured discharge range. QMLE is nearly unbiased for moderate values of the measured discharge range, but shows increasingly positive bias for either large or small value of the measured discharge range. MVUE is unbiased. It is also analyzed how the estimated regression coefficient and exponent are distributed along Nakdong river main stream.
Keywords
Load estimation; Nakdong river; Regression; Suspended solid;
Citations & Related Records
Times Cited By KSCI : 4  (Citation Analysis)
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