similar to: studentized residues from nls()

Hi there, I hope I can get advice regarding the calculation of leverage values or studentized residual values of a non-linear regression model. It seems like rstudent() does not work on a nls object. Many thanks in advance! Best regards, Xingli

Hello folks, I'm seeking opinions about the validity of the following use of the nls function... A colleague and myself are working with tree allometric data consisting of measurements of individual trees in semi-arid Australian woodland species. We need to make predictions of trunk diameter (DBH: diameter at breast height) given tree height and vice versa. I _think_ this falls into the

Dear List, I'm aware that this has been brought up before (e.g. <http://tolstoy.newcastle.edu.au/R/e6/help/09/03/7365.html> http://tolstoy.newcastle.edu.au/R/e6/help/09/03/7365.html ; <https://stat.ethz.ch/pipermail/r-help/2009-March/190902.html> https://stat.ethz.ch/pipermail/r-help/2009-March/190902.html), I couldn't find anything recent on the topic, though. After

Hello, I have encountered problems using odfdWeave. I actually have the same error message as was reported in this message ( http://tolstoy.newcastle.edu.au/R/e6/help/09/01/0872.html), but I don't quite understand the answer made by Max Kuhn ("You need to cat the results using odfCAt, otherwise you are just writing the output with no XML around it."). What I am supposed to do

Folks, An RUnit test suite is failing after all tests are complete with the following message: Error in parse(n = -1, file = file) : unexpected '}' at 620: 621: } All individual tests work when run individually, and all but one run within the RUnit test suite. What might be causing this? A similar error message during package creation was discussed earlier

Is there a way to display something like the quadratic equation, i.e. with a numerator and demonator on a plot? I think there is a way to create the equation in Latex, but wasn't sure if this format would translate to plotting. \begin{equation} ? x = \frac{b +/- sqrt(b^2 - 4*a*c)}{2*a} \end{equation} ? My searched turned up the following:

This report follows the post http://tolstoy.newcastle.edu.au/R/e6/devel/09/03/0760.html where it is shown that quantile() and IQR() do not work as documented. In fact they do not check for numeric input even if the documentation says = : ?quantile x numeric vectors whose sample quantiles are wanted. Missing values are ignored. ?IQR x a numeric vector. > quantile(factor(1:9)) 0%

Hello list, I have a similar issue as this post http://tolstoy.newcastle.edu.au/R/e6/help/09/04/11438.html#options2 and I used the suggestion provided by Jorge with modifications to my data do.call(c,lapply(your_list_with_the_t_tests,function(x) x$p.value)) but I am getting the following error after excuting the code B<-by(eo,eo$PlateID, function(.sub) t.test(mcp1~Self_T1D,data=.sub,

Dear useRs, Some time ago I queried the list as to an efficient way of building a function which acts as ls() but with a different default for all.names: http://tolstoy.newcastle.edu.au/R/e6/help/09/03/7588.html I have struck upon a solution which so far has performed admirably. In particular, it uses ls() and not its explicit source code, so only has a dependency on its name and the name of

Hi, It seems to me that the most suitable method in R for curve-fitting is the use of nls, which uses a Gauss-Newton (GN) algorithm, while the use of the Levenberg-Marquardt (LM) algorithm does not seem to be very stressed in R. According to this [1] by Ripley, 'Levenberg-Marquardt is hardly competitive these days' which could imply the low emphasize on LM in R. The position of LM is, to

Hi, First, let me thank Jaroslaw for making this survey. I find it quite illuminating. Now the questions: * the #1 solution below (based on cumsum) is numerically unstable. Specifically if you do the runmean on a positive vector you can easily get negative numbers due to rounding errors. Does anyone see a modification which is free of this deficiency? * is it possible to optimize the

Dear members of the list, I'm a beginner in R and I'm having some trouble with: "Error in optim(init[mask], armafn, method = "BFGS", hessian = TRUE, control = optim.control, : non-finite finite-difference value [8]" when running "arima". I've seen that some people have come accross the same problem:

I have a data set like this in one .txt file (cols separated by !): APE!KKU!684! APE!VAL!! APE!UASU!! APE!PLA!1! APE!E!10! APE!TPVA!17122009! APE!STAP!1! GG!KK!KK! APE!KKU!684! APE!VAL!! APE!UASU!! APE!PLA!1! APE!E!10! APE!TPVA!17122009! APE!STAP!1! GG!KK!KK! APE!KKU!684! APE!VAL!! APE!UASU!! APE!PLA!1! APE!E!10! APE!TPVA!17122009! APE!STAP!1! GG!KK!KK! it contains over 14 000 000 records. Now

Hi list, I was trying to use "predict.coxph" to calculate martingale residuals on a test data, however, as pointed out before http://tolstoy.newcastle.edu.au/R/e4/help/08/06/13508.html predict(mycox1, newdata, type="expected") is not implemented yet. Dieter suggested to use 'cph' and 'predict.Design', but from my reading so far, I'm not sure they can

Dear members of the list, I''m a beginner in R and I''m having some trouble with: "Error in optim(init[mask], armafn, method = "BFGS", hessian = TRUE, control = optim.control, : non-finite finite-difference value [8]" when running "arima". I''ve seen that some people have come accross the same problem:

Hi, I've been trying to pass a character vector from R to a FORTRAN subroutine. There have been several posts discussing this issue (e.g. http://tolstoy.newcastle.edu.au/R/help/98a/0547.html, http://tolstoy.newcastle.edu.au/R/help/05/10/13558.html, http://tolstoy.newcastle.edu.au/R/help/01a/2577.html, http://tolstoy.newcastle.edu.au/R/help/01c/1795.html,

Dear R users, this is a follow up of this message http://tolstoy.newcastle.edu.au/R/e6/help/09/05/13897.html I'm reproducing the core of it for convenience. > // > / data(Oats, package = "MEMSS") / > / tp1.oats <- xyplot(yield ~ nitro | Variety + Block, / > / data = Oats, / > / panel = function(x, y, subscripts, ...) { /

From: Uwe Ligges <ligges_at_statistik.tu-dortmund.de <mailto:ligges_at_statistik.tu-dortmund.de?Subject=Re:%20[R]%20Help%20with%2 0gam> > Date: Wed, 11 May 2011 19:08:38 +0200 On 11.05.2011 17:22, Zsolt Macskasi wrote: > Hi, > <http://tolstoy.newcastle.edu.au/R/e14/help/11/05/1036.html#1040qlink1> > I am a brand new user of R and I am trying to use the gam

Full_Name: Henrik Aalborg Nielsen Version: 2.10 OS: Linux (SLES 10 / openSUSE 11.1) Submission from: (NULL) (77.66.63.89) There seems to be a bug in df.residual.nls which is triggered when nls is called with argument na.action = na.exclude; in that case 'resid(object)' will contain NA-values which should be disregarded when counting the number of residuals: df.residual.nls <-

Dear R-listers, I would like to know if there is a way to programmatically generate parameter start values for the model y~(a*exp(b*x)+c*exp(d*x)) in R. I've scoured the help files and archives for nls() and similar searches, and have read Fox 2002 - the best advice has been to make estimates from a priori knowledge of the data. However, in the Matlab CurveFit tool, reliable start values are