[SciPy-User] calculate predicted values from regression + confidence intervall

[Christian K.]

Hi Joseph,

<josef.pktd <at> gmail.com> writes:
> 
> Roughly (I would need to check the details):
> the parameter estimate is from a multivariate normal distribution,
> your y is a linear transformation, so the prediction should be normal
> distributed with mean y = Y = X*beta, and var(y) = X' * cov_beta * X +
> var_u_estimate (dot products for appropriate shapes)

Does this hold also for nonlinear models? I would need to calculate prediction 
intervals for something like

f(X,Y) = a1-a2*log(X)+a3/Y (inverse power/Arrhenius model from accelerated 
reliability testing)

Currently I am using a Monte Carllo approach to get the prediction intervals.

Best regards, Christian K.