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Adjustment of Prediction Intervals in Nonlinear Regression
Author(s) -
Goh K. L.,
Pooi A. H.
Publication year - 1997
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.4710390610
Subject(s) - mathematics , quadratic equation , nonlinear regression , nonlinear system , statistics , prediction interval , regression , regression analysis , physics , geometry , quantum mechanics
By treating the nonlinear model as if it were linear in the parameterization θ in the neighbourhood of the least squares estimate θC, two‐sided nominally‐ q ‐prediction intervals can be constructed by applying the usual linear model theory. The quadratic approximation of the expected coverage of the prediction intervals is derived for a p ‐parameter nonlinear model. An adjustment of the nominally‐ q ‐prediction intervals is proposed. It is shown that, to the extent that quadratic approximation is adequate, the actual expected coverage of the adjusted prediction intervals is q .