similar to: How to compare fit of linear and nonlinear models

G'morning What does the error message "Error in x %*% coef(object) : non- conformable arguments" indicate when calculating the response values for newdata with a model from bigglm (in package biglm), and how can I debug it? I am attempting to do Monte Carlo simulations, which may explain the loop in the code that follows. After the code I have included the output, which shows that

Hello, and thanks in advance! What does the error message "Error in x %*% coef(object) : non- conformable arguments" when indicate when predicting values for newdata with a model from bigglm (in package biglm), and how can I debug it? I am attempting to do Monte Carlo simulations, which may explain the somewhat interesting loop which follows. After the code I have included the output,

I have a question regarding robust nonlinear regression with nlrob. I would like to place lower bounds on the parameters, but when I call nlrob with limits it returns the following error: "Error in psi(resid/Scale, ...) : unused argument(s) (lower = list(Asym = 1, mid = 1, scal = 1))" After consulting the documentation I noticed that upper and lower are not listed as parameter in

In order to bootstrap nonlinear regression, the following code works. library(nlme) data(Soybean) fm1.nls <- nls(weight ~ SSlogis(Time, a, b, c), data=Soybean) summary(fm1.nls) bstat <- function(A, indices) { mboot <- nls(weight ~ SSlogis(Time, a, b, c), data=Soybean[indices, ]) return(coef(mboot)) } require(boot) boot1 <- boot(Soybean, bstat, 2000) boot1 For nonlinear mixed

>>>>> PIKAL Petr <petr.pikal at precheza.cz> >>>>> on Fri, 20 Oct 2017 06:33:36 +0000 writes: > Hi > Keep your messages in the list, you increase your chance to get some answer. > I changed your data to groupedData object (see below), but I did not find any problem in it. > plot(wlg) > gives reasonable picture and I am

Dear all, I encounter some discrepancies when comparing the deviance of a weighted and unweigthed model with the AIC values. A general example (from 'nls'): DNase1 <- subset(DNase, Run == 1) fm1DNase1 <- nls(density ~ SSlogis(log(conc), Asym, xmid, scal), DNase1) This is the unweighted fit, in the code of 'nls' one can see that 'nls' generates a vector

Hi all, I am trying to use nonlinear regression (nls) to analyze some seed germination data, but am having problems with error codes. The data that I have closely matches the germination dataset included in the drc package. Here is the head of the data temp species start end germinated TotSeeds TotGerminated Prop 1 10 wheat 0 1 0 20 0 0.0 2 10 wheat

Hi all I?m trying to get confidence intervals for parameters from nls modeling. I fitted a nls model to the following variables: > x [1] 2 1 1 5 4 6 13 11 13 101 101 101 > y [1] 1.281055090 1.563609934 0.001570796 2.291579783 0.841891853 [6] 6.553951324 14.243274230 14.519899320 15.066473610 21.728809880 [11] 18.553054450 23.722637370 The model fitted was:

Hi, I am trying to run the following nonlinear regression model. > nreg <- nls(y ~ exp(-b*x), data = mydf, start = list(b = 0), alg = "default", trace = TRUE) OUTPUT: 24619327 : 0 24593178 : 0.0001166910 24555219 : 0.0005019005 24521810 : 0.001341571 24500774 : 0.002705402 24490713 : 0.004401078 24486658 : 0.00607728 24485115 : 0.007484372

Thank you Martin. If I understand correctly, OP could do wheat.list <- nlsList(Prop ~ SSfpl(end, A, B, xmid, scal), data=wlg) or add some small value to all zeroes wlg$prop < -wlg$Prop+1e-7 wheat.list <- nlsList(prop ~ SSlogis(end,Asym, xmid, scal), data=wlg) which gives fairly reasonable results. plot(augPred(wheat.list)) Am I correct? Cheers Petr > -----Original Message-----

Hi Keep your messages in the list, you increase your chance to get some answer. I changed your data to groupedData object (see below), but I did not find any problem in it. plot(wlg) gives reasonable picture and I am not such expert to see any problem with data. Seems to me, that something has to be wrong with nlsList function. > wheat.list <- nlsList(Prop ~ SSlogis(end,Asym, xmid,

Hi!! Can anyone help me, i have problems to converge the following data with 5 nonlinears models that i evaluated. Firtly, i send my data (totalsinatipicos) that i just try to fit with the nonlinear models. Next, i have the following script where i called the data as totalsinatipicos. I made selfstarting each nonlinear model. ###Library library(NRAIA) ###Data d<-totalsinatipicos

Hi Aki, Am 21.02.19 um 12:55 schrieb Aki Tuomi: > > On 21.2.2019 13.47, Lionel Elie Mamane via dovecot wrote: >> I noticed a mail stuck in my mail queue. dovecot-lda was returning >> error 64 Invalid parameter given. (EX_USAGE). >> >> Weird, weird, weird. After some sleuthing, I found the sender address >> was FirstLast at domain.tld, with a UTF8-encoded

Hi R community I have a little problem, and I tried to solve it by myself but I couldn't. I building an if loop, and I want to check a value inside an interval. This would be the case: pvalue=0,2999 if(pvalue>0.05 or pvalue<0.1) as you can see I would like to check in that if loop if my pvalue is inside of that interval(from 0.05 to 0.1), and I tried these options: if(pvalue>0.05

R-64 latest Hi. I am trying to plot a set of csv data, which looks like > head(interval) date inteval 1 2012-07-01 00:57:54 +0900 156 2 2012-07-01 01:07:41 +0900 587 3 2012-07-01 01:09:31 +0900 110 4 2012-07-01 01:18:42 +0900 551 5 2012-07-01 01:39:01 +0900 1219 6 2012-07-01 01:40:40 +0900 99 as you can see, more than one event happens each day,

Full_Name: Hendrik Weisser Version: 2.6.1 OS: Linux Submission from: (NULL) (139.19.102.218) The following computation never finishes and locks R up: > values <- list(x=10:30, y=c(23.85, 28.805, 28.195, 26.23, 25.005, 20.475, 17.33, 14.97, 11.765, 8.857, 5.3725, 5.16, 4.2105, 2.929, 2.174, 1.25, 1.0255, 0.612, 0.556, 0.4025, 0.173)) > y.max <- max(values$y) > model <- nls(y ~

Hi, I think this is a problem solved but I would be interested to know if there is some good reason why SSlogis() behaves like this (apologies if this has been noticed before- I'm not confident my archive searches were effective): I have been fitting large numbers of regressions using nls with a self-starting 3 parameter logistic model (SSlogis()). I got a series of unexpected errors of the

Hello there! I got some data with x and y values. there are some y == 0. This is a problem for the selfstarting regression model SSlogis. The regression works if I use a non selfstarting model. The formula is the same. But this needs very detailed information of the starting list. I dont have this Information all the time. An easy solution for selfstart model could be to add 1E-100 to the y==0

Hi R help, I am trying to determine how nls() generates a function based on the self-starting SSlogis and what the formula for the function would be. I've scoured the help site, and other literature to try and figure this out but I still am unsure if I am correct in what I am coming up with. ************************************************************************** dat <-

Hello everybody, I am hoping you can help me. I just downloaded and installed the "precompiled binary distribution" of R to my Windows machine (running Windows Millennium). (I did not download or install anything else - no packages). I need to run a logistic regression and understand the function I need is polr() or maybe SSlogis(). However, when I try to invoke either function,