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Hydrologic regression with weighted least squares
Author(s) -
Tasker Gary D.
Publication year - 1980
Publication title -
water resources research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.863
H-Index - 217
eISSN - 1944-7973
pISSN - 0043-1397
DOI - 10.1029/wr016i006p01107
Subject(s) - ordinary least squares , statistics , weighting , regression , mathematics , regression analysis , total least squares , partial least squares regression , linear regression , standard error , generalized least squares , least squares function approximation , robust regression , physics , estimator , acoustics
Ordinary least squares (OLS) regression and weighted least squares (WLS) regression are compared by simulating a model of the form Q 50 =α A β1 , where Q 50 is the 50‐year peak discharge, A is drainage area, and α and β 1 are regional parameters estimated from a regression of observed 50‐year peaks at gaging stations. Results indicate that OLS has a larger expected standard error of prediction than WLS when the following weighting function is used: for i = 1, 2,…, N , where ĉ 0 and ĉ 1 are constants estimated from sample data, n i , is the record length of station i , N is the number of stations, and ŵ i , is the weight given to data for station i .