search for: beta1x1

..., 1, 1, 3, 2, 3, 3, 0, 2), y = c(1.4287, 1.4426, 1.4677, 1.4774, 1.4565, 1.4807, 1.4279, 1.4684, 1.4301, 1.4188, 1.4157, 1.4686, 1.4414, 1.4172, 1.4829, 1.4291, 1.4438, 1.4068, 1.4524, 1.4183)), row.names = c(NA, -20L), class = "data.frame") The model is the following: y = 1/(Beta1x1 + Beta2x2 + Beta3x3) I need to determine starting (initial) values for the model parameters for this nonlinear regression model, any ideas on how to accomplish this using R? Cheers, Paul [[alternative HTML version deleted]]

...> > 1.4807, 1.4279, 1.4684, 1.4301, 1.4188, 1.4157, 1.4686, 1.4414, > > 1.4172, 1.4829, 1.4291, 1.4438, 1.4068, 1.4524, 1.4183)), row.names > = > > c(NA, > > -20L), class = "data.frame") > > > > The model is the following: > > y = 1/(Beta1x1 + Beta2x2 + Beta3x3) > > > > I need to determine starting (initial) values for the model parameters > for > > this nonlinear regression model, any ideas on how to accomplish this > using > > R? > > > > Cheers, > > Paul > > > > [[alte...

....4279, 1.4684, 1.4301, 1.4188, 1.4157, 1.4686, 1.4414, > >? ? ? 1.4172, 1.4829, 1.4291, 1.4438, 1.4068, 1.4524, 1.4183)), row.names = > > c(NA, > > -20L), class = "data.frame") > > > > The model is the following: > > y = 1/(Beta1x1 + Beta2x2 + Beta3x3) > > > > I need to determine starting (initial) values for the model parameters for > > this nonlinear regression model, any ideas on how to accomplish this using > > R? > > > > Cheers, > > Paul >...

Dear all, This is a pure statistical question, not necessarly related to R. I could not find it in literature. Suppose I'm intersted in a parameter rho, say, equal to: r=beta1/beta2, where beta1 and beta2 come from a linear model y=beta0+beta1X1+beta2X2+.... Fitting the model I can get the (biased) estimate of r=b1/b2, where b1 and b2 are the estimates in the regression model; I can get the unbiased estimate of rho as well as its SE using the delta method. I'm interested in confidence interval for r. A simple method could be (I suppose...