search for: nonlin

Hi all I want to construct a generalised nonlinear model (binomial family) using gnm, of the form: Response = a + b variable1 + c variable2 + d variable3 - d b variable4 - d c variable5, with the parameters b, c, and d appearing more than once. Hence, I think I need to use a custom nonlin function with gnm. One of my predictor variables is ca...

I have been trying to port the extension 'nlme' ("Classes and methods to fit and display linear and nonlinear mixed effects models.")to R found on the Statlib S site. I am having some difficulty. The c code requires at least S.h and nonlin.h. R has S.h but not nonlin.h. I'm only a recent convert to R, and have not used S nor SPlus. Any help is greatly appreciated. Gerry -.-.-.-.-.-....

Hi, I am an old hand at chemistry but a complete beginner at statistics including R computations. My question is whether you can carry out nonlinear multivariate regression analysis in R using neural networks, where the output variable can range from -Inf to + Inf., unlike discriminant analysis where the output is confined to one or zero. The library nnet seems to work only in the latter case but then I could be wrong. Please help me...

...>> Surv(START, STOP, ZEROBAL == 1) ~ pspline(OPTION),> data = FNMA)> >> coef se(coef) se2 Chisq DF >> p> pspline(OPTION), linear -0.1334 0.0131 0.0131 104.4325 >> 1.00 <0.0000000000000002> pspline(OPTION), nonlin >> 1747.1295 3.05 <0.0000000000000002> Iterations: 8 outer, 19 >> Newton-Raphson> Theta= 0.991> Degrees of freedom for terms= 4> >> Likelihood ratio test=2136 on 4.05 df, p=0 n= 3390429* > > > > What I do not understand, and what I have not fo...

...(formula = > Surv(START, STOP, ZEROBAL == 1) ~ pspline(OPTION), > data = FNMA)> > coef se(coef) se2 Chisq DF > p> pspline(OPTION), linear -0.1334 0.0131 0.0131 104.4325 > 1.00 <0.0000000000000002> pspline(OPTION), nonlin > 1747.1295 3.05 <0.0000000000000002> Iterations: 8 outer, 19 > Newton-Raphson> Theta= 0.991 > Degrees of freedom for terms= 4 > > Likelihood ratio test=2136 on 4.05 df, p=0 n= 3390429 > * Thanks, KS [[alternative HTML version deleted]]

...e specification of the analysis on a list of some sort as well. For example: List "a" has 3 zoo data sets and list "b" has 2 specifications (calls) for a function (say, "analysis(specification, inputdata)" ) that runs some statistical manipulations (regressions, nonlin models, etc. etc.) on the elements of the zoo data frames. Thus I want to be able to run (this is pseudo R code): for (i in 1:3) { output1<-analysis(b[1], a[i]) output2<-analysis(b[2], a[i]) } Thanks in advance for any pointers or help. Best, Costas [[alternative HTML version dele...

Hello R-helpers, I would like to fit a non-linear function to data (Discrete X axis, over-dispersed Poisson values on the Y axis). I found the functions gnlr in the gnlm package from Jim Lindsey: this can handle nonlinear regression equations for the parameters of Poisson and negative binomial distributions, among others. I also found the function nls2 in the software package accompanying the book "Statistical tools for nonlinear regression" by Huet et al: this can handle nonlinear regression wi...

...ts null hypothesis that the spline coefficient is the same at the center of basis. Thus, in the example quoted below (from the thread) one might say treating age as linear is not too bad, to the extent that failure to reject a null can be so interpreted. Is that right? And what is the null for the nonlinear test? --Michael Margolis ..............QUOTE.............. Use pspline within a Cox model. It includes a fairly general test for nonlinearity, that is similar to GAM models. Terry Therneau > coxph(Surv(time, status) ~ ph.ecog + pspline(age), lung) Call: coxph(formula = Surv(time,...

Hi, recently I saw but did not pay too much attention to a question that concerned regression with positive coefficients. In Splus, thereis the nnls() function that can be used if I am not wrong, but what about R ? Now I have the same problem: doing a logistic regression under constraint that coefs are non negative. What can I do with R? is there a (weighted) nnls() counterpart available? Thanks

Hi, I am just wondering if there is a test available for testing if a linear fit of an independent variable in a Cox regression is enough? Thanks for any suggestions. John Zhang ____________________________________________________________________________________ [[elided Yahoo spam]]

...ask the guy for an official port.) time.series (Paul Gilbert promised an official release following the release of R 0.50) Fritz (and I) have also started to port the `clus' software which was recently documented in an article in Journal of Statistical Software. Also, Doug's nonlin seems to compute fine after one change, but the output needs help. Is this still useful, or do we have something better for fitting nonlinear models? As you can see from the list, we're not doing too bad ... -k =-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=- r...

...RCE=2 -fexceptions -fstack-protector --param=ssp-buffer-size=4 -m32 -march=i386 -mtune=generic -fasynchronous-unwind-tables -c corStruct.c -o corStruct.o In file included from matrix.h:25, from corStruct.c:25: base.h:27:28: error: S.h: No such file or directory base.h:43:20: error: nonlin.h: No such file or directory In file included from matrix.h:25, from corStruct.c:25: base.h:56: error: 'F77_NAME' declared as function returning a function base.h:56: warning: parameter names (without types) in function declaration base.h:57: error: 'F77_NAME' decla...

Hello to all, I'm a biologist trying to tackle a "fish" (Poisson Regression) which is just too big for my modest understanding of stats!!! Here goes... I want to find good literature or proper mathematical procedure to calculate a confidence interval for an inverse prediction of a Poisson regression using R. I'm currently trying to analyse a "dose-response"