Abstract
Standard Wald confidence regions for parameters in a normal nonlinear regression model often fail to capture accurately the uncertainty of estimation as reflected by the corresponding profile log-likelihood. We present a graphical method, along with a stable computational algorithm, for inference on scalar parameters in a nonlinear regression model. © 1990 Taylor & Francis Group, LLC.
Original language | English (US) |
---|---|
Pages (from-to) | 544-551 |
Number of pages | 8 |
Journal | Journal of the American Statistical Association |
Volume | 85 |
Issue number | 410 |
DOIs | |
State | Published - 1990 |