similar to: nls: formula error?

Hello, I hope this doesn't turn into a statistics question but here I go. I am using the nls function with a Gaussian distribution, see coding below. When I run the nls I get an error back saying that I have a linear gradient. I then, of course am unable to do anything else. The data that I am using are intensity values from some mass spectrometry data. Is there something I can

Ok I guess it's time to ask. So I want to plot my data. It's my data from a frequency table, "temp". My formula is just a Gaussian eq. I have done the nls function to get my parameters and now I want to do the whole plot (...) and then lines(..) This is what I have done. > temp bin x 1 -4.0 0 2 -3.9 0 3 -3.8 0 4 -3.7 0 5 -3.6 0 6 -3.5 0 .... and so

Hello, I'm doing some scripting and I've noticed that R doesn't seem to have an if (cond){ do }ifelse (cond) { do } else { do } type block. Is this correct or am I missing something. THX Paul -- Research Technician Mass Spectrometry o The / o Scripps \ o Research / o Institute

A colleague of mine is trying to use nls() to effect an optimization, and is encountering a scoping problem. I should know how to solve it for him but .... well, I just don't. I also had a quick scrounge of the archives --- I know I've seen this topic addressed before --- but I couldn't track it down. So here's a toy example that demonstrates the problem: hhh <-

Hello, I am trying to bootstrap a function that extracts the log-likelihood value and the nls coefficients from an nls object. I want to sample my dataset (pdd) with replacement and for each sampled dataset, I want to run nls and output the nls coefficients and the log-likelihood value. Code: x<-c(1,2,3,4,5,6,7,8,9,10) y<-c(10,11,12,15,19,23,26,28,28,30) pdd<-data.frame(x,y)

Hello, In doing a series of non-linear estimations of a function which is a sum of a varying number of sinusoids, I would like to "autogenerate" the arguments needed by nls() depending on that number. For example, when there are two sinusoids: > nls( y ~ mu + A1 * cos(2*pi*f1*x - P1) + A2 * cos(2*pi*f2*x - P2), data = some.xy.data, start = list( mu=some.value0,

Hello, Sorry to all for the lack of communication, and thanks to those with the suggestions. So I have two matrixes which are different sizes, same column number but different row number. What I would like to do is to compare A to B. In the 6 and 9th column there are ref numbers (molecular masses to be exact). I would like to check A and B by these columns. If I find that the number in A[9,x]

Full_Name: Michael Montero Version: 1011 OS: NT4.0 Submission from: (NULL) (128.32.148.191) I haven't been able to use the nls() function because of the following error: Error in eval.with.vis(expr, envir, enclos) : couldn't find function "nls" Apparently nls() is no where to be found, in the /library directory nls exists with all its files.. need help.. thanks

Hi Everyone, I posted this a couple of weeks ago with no responses. My interface (via gmane) seemed a bit flakey at the time, so I'm venturing to repost with some additional information. I'm trying to write selfStart non-linear models for use with nls. In these models some combinations of parameter values are illegal; the function value is undefined. That's OK when calling the

I'm drawing a fitted normal distribution over a histogram. The use case is trivial (fitting normal distributions on densities) but I want to extend it to other fitting scenarios. What has stumped me so far is how to take the list that is returned by nls() and use it for curve(). I realize that I can easily do all of this with a few intermediate steps for any specific case. But I had expected

Dear All, I have a matrix with data that is not organised. I would like to go through this and extract it. Each feature has 2 vectors which express the data. I also have an index of the places where the data should be cut. eg. >class(cc) "matrix" >cc [,1] [,2] [1,] 1 26 [2,] 2 27 [3,] 3 28 [4,] 4 29 [5,] 5 30 [6,] 6 31 [7,] 7 32

I'm tyring to fit a relatively simple nls model to some data, but keep coming up against the same error (code follows): Oto=nls(Otolith ~ Linf*(1-exp(-k(AGE-to))), data = ages, start = list(Linf=1000, k=0.1, to=0.1), trace = TRUE) The error message I keep getting is "Error in eval(expr, envir, enclos) : could not find function "k"". I've used this

Hello, I apologise if someone has already answered this but I searched and googled but didn't find anything. I have a matrix which gives me the similarity of each item to each other. I would like to turn this matrix into something like what they have in the graph package with the nodes and edges. http://cran.r-project.org/doc/packages/graph.pdf . However I cannot find a method to

I haven't followed your example closely, but can't you use the predict() method for this? To draw a curve, the function that will be used in curve() sets up a newdata dataframe and passes it to predict(fit, newdata= ...) to get predictions at those locations. Duncan Murdoch On 17/10/2020 5:27 a.m., Boris Steipe wrote: > I'm drawing a fitted normal distribution over a

Dear R-Helpers, I'm working with immunoassay data and 5PL logistic model. I wanted to experiment with different forms of weighting and parameter selection, which is not possible in instrument software, so I turned to R. I am using R 2.14.2 under Win7 64bit, and the 'nls' library to fit the model - I started with the same model and weighting type (1/y) as in the instrument to see

Umm sorry to bother everyone again but I'm having trouble with my if statement. I come from a perl background so that's probably my problem! :) So here is my code: if (any(lgAB>4) | any(lgAB<-4)){ freq_AB<-hist(lgAB, type="o", plot=F) else freq_AB<-hist(lgAB, breaks=br,type ="o", plot=F) } And I get > source("E:/R/GMDA-1.1.R") Error in

Error in model.frame When I run the following nls model an error message appears and I dont know how to solve that. Could you help me?? mat = c(1,2,3,4,5,6,7,8,9,12,16,24,36,48,60) for (i in 1:length(j30)) { bliss = nls(c(j[i,1:length(mat)]) ~ b0 + b1*((1-exp(-k1*mat))/(k1*mat)) + b2*(((1-exp(-k2*mat))/(k2*mat))-exp(-k2*mat)), start = list(k1=0.1993, k2=0.1993, b0= 22.0046,

Hello all, I know this is a pretty easy question but I can't find it in S poetry or R help. How can I make a negative number positive. Such as -5 to be +5 I tried +(-5), but that didn't work. So no, I don't mean taking a -5^2 just to get a positive number. This is in a function so it's not just -5 it's x. :) Thanks, Paul -- Research Technician Mass Spectrometry o The

List gurus, I'm trying to code a Gompertz growth curve function as part of a larger project and have run across a problem due to my ignorance of environments. Some sample data and the function are as follows: growth <- data.frame(age = c(1.92, 3, 5.83, 3.17, 15.5, 1.17, 5.58, 13.33, 14.29, 5.83, 13.79, 6.33, 13.75, 16.83, 13, 11.67, 0.25, 1.73, 9.46, 5.67), length = c(157, 165, 179,

Hello All, I have searched but haven't been able to find an answer to this question. I'm writing a function that needs to be able evaluate the right-hand side of a general non-linear formula for different parameter values, similar to what nls() does. I looked through the nls() code but it isn't clear what is going on. Could someone point me to a reference or a way I might do this?