search for: errk1

....4628794 0.4688428 0.001973953 : 0.4628974 0.4682051 Nonlinear regression model model: noisy ~ lsoda(xstart, time, one.compartment.model, c(K1 = K1, k2 = k2))[, 2] data: C1.lsoda K1 k2 0.4628974 0.4682051 (-7%) (-6%) residual sum-of-squares: 0.001973953 > errK1=(0.4628974-0.5)/0.5 > errK1 [1] -0.0742052 > errk1=(0.4682051-0.5)/0.5 > errk1 [1] -0.0635898 Oscar Oscar A. Linares, MD, PhD Prof. Experimental Medicine Michigan Diabetes Institute olinares at med.umich.edu Oscar A. Linares, MD, PhD /////// Michigan Diabetes Institute S c...

Dear all I have tried to estimate the confidence intervals for predicted values of a nonlinear model fitted with nls. The function predict gives the predicted values and the lower and upper limits of the prediction, when the class of the object is lm or glm. When the object is derived from nls, the function predict (or predict.nls) gives only the predicted values. The se.fit and interval aguments