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Improved Identification of Parameters in the Wolgograd Growth Model for Sugar Beets
Author(s) -
Tittel B.,
Toutenburg H.
Publication year - 1983
Publication title -
biometrical journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.108
H-Index - 63
eISSN - 1521-4036
pISSN - 0323-3847
DOI - 10.1002/bimj.19830250304
Subject(s) - multicollinearity , mathematics , minimax , estimator , minimax estimator , statistics , goodness of fit , logarithm , linear regression , econometrics , minimum variance unbiased estimator , mathematical optimization , mathematical analysis
Starting point of the investigations is the time‐invariant Wolgograd model applied to a sample of sugar beets. To overcome the weak multicollinearity of the model in its logarithmic form, a ridge‐type estimator is applied which uses prior information on the unknown regression coefficients. This is done by introducing the biased minimax‐linear estimator. To judge the goodness of the estimates there are calculated the minimax risks of the MILE and the OLSE as well as the estimated maximal crop yields.