similar to: How to write a package based on nlme

Hi folks, I am tearing my hair out on this one. I am using an example from Pinheiro and Bates. ### this works data(Orange) mod.lis <- nlsList(circumference ~ SSlogis(age, Asymp, xmid, scal), data=Orange ) ### This works mod <- nlme(circumference ~ SSlogis(age, Asymp, xmid, scal), data=Orange, fixed = Asymp + xmid + scal ~ 1, start =

Hi List, While using 'nlme' function, I have encountered the similar problem Dr. Stevens and Dr. Graves observed (please see the posts: https://stat.ethz.ch/pipermail/r-help/2006-May/105832.html ). I have tried Dr. Stevens's original example, the problem is still there, > mod.lis <- nlsList(circumference ~ SSlogis(age, Asymp, xmid, scal), + data=Orange ) >

Dear List, I will appreciate any advice regarding how to convert the following numbers [I got in return by taxondive()] in numeric integers without the e.g. 6.4836e+01 abbreviations. Thank you very much in advance, Gian > taxa_dive Species Delta Delta* Lambda+ Delta+ S Delta+ Nat1 5.0000e+00 6.4836e+01 9.5412e+01 6.7753e+02 8.7398e+01 436.99 Nat2

Last Friday, Gregory Chaitin (http://www.umcs.maine.edu/~chaitin/lm.html) mentioned that there can be no proof that a given code is the shortest for a problem, even within a language. Still, the script below, a replacement of the "TDT", one of the most frequently used tests in genetics (http://mustat.rockefeller.edu under "downloads") may get close. It contains a few

Hi, I have a program written in R which is good on the version 1.2, but for the fallowing versions of R, an error always is at the same place. That is at the level of the fallowing line: Sur<- getInitial(res2[m:M,2]~SSasymp(res2[m:M,1],Asymp,resp0,lrc),data=res2) Error in eval(expr,envir,enclos):numeric envir arg not of length one I don't know at all this langage for the instant.

I'm trying to use a paper by Hardin & Rocke: http://handel.cipic.ucdavis.edu/~dmrocke/Robdist5.pdf as a guide for a function to identify outliers in multivariate data. Attached below is a function that is my attempt to reproduce their method and also a test to see what fraction of the data are identified as outliers. Using this function I am able to reproduce their results regarding the

Hello List, I`m trying to make prediction using a bagged tree with the package ipred. I tried to follow the manual but I`m getting an error message. Also browsing through the list-archive I didn`t find any hint. Maybe someone can help me? selbag <- bagging(SOIL_UNIT ~., data=traindat.bin, coob=TRUE) Error in dimnames(X) <- list(dn[[1L]], unlist(collabs, use.names = FALSE)) :

I made one typo in my previous mail.   May I ask one statistics related question please? I have one query on MLE itself. It's property says that, for large sample size it is normally distributed [i.e. asymptotically normal]. On the other hand it is "Consistent" as well. My doubt is, how this two asymptotic properties exist simultaneously? If it is consistent then asymptotically it

Hi list, I tried to load the package SAGx and failed because it complains it's looking for the Biobass which is not there. Then I looked up the package list and Biobass is not found. I'm trying to run the Jonckheere-Terpstra test and from what I see in the R archive, SAGx is the only place it's been implemented. > library(SAGx) Loading required package: multtest Loading required

Hello, I am hoping someone can clarify why I might obtain a quite different value in R & SPSS for a McNemar test I ran. Firstly, here is the R syntax & output R OUTPUT > mctest <- as.table(matrix(c(128,29,331,430), + ncol =2, dimnames = list(group=c("preMHT","postMHT"), + assault=c("yes","no")))) > mctest assault

Hello. I am trying to fit an asymptotic relationship (nonlinear) to some ecological data, and am having problems. I am interested in the upper bound on the data (i.e. if there is an upper limit to 'y' across a range of 'x'). As such, I am using the nonlinear quantile regression package (nlrq) to fit a michaelis mention type model. The errors I get (which are dependant on

Hey, all. I'm working on a data set with a broken stick linear regression where I know one of the two slopes. It is a negative linear function until the line intersects with the x-axis, at which point it becomes 0. It is not a nonlinear asymptotic function, and, indeed, using negative exponential or logistic types of fits as an approximation has tended to lead to an under or

Hi all, I would like to predict some values for an nls regression function (functional response model Rogers type II). This is an asymptotic function of which I would like to predict the asymptotic value I estimated the paramters with nls, but can't seem to get predictions for values of m choice...... This is my script: RogersII_N <-

May I ask one statistics related question please? I have one query on MLE itself. It's property says that, for large sample size it is normally distributed [i.e. asymptotically normal]. On the other hand it is Efficient as well. My doubt is, how this two asymptotic properties exist simultaneously? If it is consistent then asymptotically it should collapse to "truth" i.e. for large

---------- Forwarded message ---------- From: <r-help-owner@r-project.org> Date: Mon, Jan 14, 2013 at 12:31 AM Subject: Help with nonlinear regression To: ahmedatia80@gmail.com The message's content type was not explicitly allowed ---------- Forwarded message ---------- From: Ahmed Attia <ahmedatia80@gmail.com> To: r-help@r-project.org Cc: Date: Mon, 14 Jan 2013 00:31:41 -0800

----------------------------------------------------------------------------------------- Packages for the computation of optimally robust estimators ----------------------------------------------------------------------------------------- We would like to announce the availability on CRAN (with possibly a minor delay until on every mirror) of new versions of our packages for the computation of

----------------------------------------------------------------------------------------- Packages for the computation of optimally robust estimators ----------------------------------------------------------------------------------------- We would like to announce the availability on CRAN (with possibly a minor delay until on every mirror) of new versions of our packages for the computation of

I'm having problems getting nls to agree that convergence has occurred in a toy problem. nls.out never gets defined when there is an error in nls. Reaching the maximum number of iterations is alway an error, so nls.out never gets defined when the maximum number of iterations is reched. >From ?nls.control: tol: A positive numeric value specifying the tolerance level for the

New package `multcomp' for general multiple comparisons written by Frank Bretz, Torsten Hothorn and Peter Westfall We've uploaded the package `multcomp' to CRAN. The R package allows for multiple comparisons of k groups in general linear models. We use the unifying representations of multiple contrast tests, which include all common multiple comparison procedures, such as the

New package `multcomp' for general multiple comparisons written by Frank Bretz, Torsten Hothorn and Peter Westfall We've uploaded the package `multcomp' to CRAN. The R package allows for multiple comparisons of k groups in general linear models. We use the unifying representations of multiple contrast tests, which include all common multiple comparison procedures, such as the