search for: gnlr3

...obviously too basic to deserve an answer - apologies for that. I'm learning, things can only get better :-) My current problem is with fitting a generalized gamma distribution with an additional "shift" parameter, that represents a shift of the distribution along the X axis. The gnlr3 function (in Jim Lindsey's GNLM package) fits this distribution in this form: f(y) = fy^(f-1)/((m/s)^(fs) Gamma(s)) y^(f(s-1)) exp(-(y s/m)^f) (1) I would like to include a fourth parameter, say u, like this: f(y) = fy^(f-1)/((m/s)^(fs) Gamma(s)) (y-u)^(f(s-1)) exp(-((y-u) s/m)^f) (2) My b...

Hi, I am quite new to R and would like to do nonlinear regressions with Poisson distributed data. I would like to estimate paramters of an equation of this type: FR = [c*NO * exp(a+b*NO)] / [(c+NO)*(1+exp(a+b*NO))] a,b and c are parameters, NO are input values I found both the gnm and gnlr3 function which should be able to do this regression but I can't manage to make it work. How can I write my equation to fit into these functions? If I understand it correct I have to split my equation in a "mu", a "shape" and a "family" part for the gnlr function...

How to fit a nonlinear regression model with power exponentially distributed errors? I know gnlm has a function gnlr3 that could work, but I would be grateful if example R code is provided. Daniel [[alternative HTML version deleted]]

Hi list, I'd like to fit generalized gamma and weibull distributions to a number of data sets. I've been searching around and found references to R and Jim Lindsey's GNLM package, which has the gnlr and gnlr3 procedures that can do this. Now, I'm completely new to R, and I'm working my way through the introduction... Nevertheless, I'd like to ask if someone could post a straightforward example of the use of gnlr/gnlr3 for simply fitting distributions (so, basically, with a null model).....

> On Wed, 2 Feb 2000, Adriane Leal wrote: > > > I'd like to perform a box-cox transformation to a data set and also plot > > lambda versus L(lambda) using R. Does anybody knows how can I do such a > > thing? gnlr3 in my gnlm library does both linear and nonlinear models with Box-Cox transformation. However, it is somewhat nonstandard as it renormalizes to obtain a true density whereas the standard transformation creates a function that is not a density because of the constraint that only positive values can...

Dear all, Are there functions or packages in R that can handle interval-censored data? I have looked in various packages (such as survival5 or event), but it seems that only right-censored data can be analysed. More generally, are there methods to analyse both interval-censored observations and right-censored observations in the same data set? Thanks in advance. Emmanuel Paradis