similar to: nls() function is not found (PR#725)

Hi all, my first post. After years with an old server, a couple of months ago I've installed a new one. We use IMAP. After research, I chosed dovecot. It has been running for several weeks but from one week ago or so, it suddently dies about once per day. The only change done in the server one week ago has been to install ntpdate, running once per day in cron-daily. In the cron

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

So thanks for the help, I have a matrix (AB) which in the first column has my bin numbers so -4 - +4 in 0.1 bin units. Then I have in the second column the frequency from some data. I have plotted them and they look roughly Gaussian. So I want to fit them/ find/optimize "mu", "sigma", and "A". So I call the nls function : nls_AB <- nls(x ~ (A/sig*sqrt(2*pi))*

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, 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)

Hi.. is there a limit on the number of explanatory variables in nls ? i have a dataframe with the columns names x1,x2..,x300 when i run nls it gives the error: " x181 not found" thought it does run when i have x1,x2,...,x170 variables. Thanks Harsh --------------------------------- [[alternative HTML version deleted]]

I'm a bit confused about the nls package, I'm trying to use it for curve fitting. First off, the documentation for nls says ``see `nlsControl' for the names of the settable control values'' -- this is wrong, it should be nls.control (minor point but had me confused for a moment). Now I'll try something very simple (maybe too simple):

Is there any problem to run icecast as a normal user? I know that if run along with liveice, I'll have to setup /dev/dsp to that user, but what about TCP/IP ports? Will it be able to run normally or I have to run it as root? Will this help in the stability of the system? This would allow a crash to only crash the user's memory space and not the system's space. Any suggestion is

Dear Friends. I tried to use nls.control() to change the 'minFactor' in nls( ), but it does not seem to work. I used nls( ) function and encountered error message "step factor 0.000488281 reduced below 'minFactor' of 0.000976563". I then tried the following: 1) Put "nls.control(minFactor = 1/(4096*128))" inside the brackets of nls, but the same error message

Dear friends. I use nls() and encounter the following puzzling problem: I have a function f(a,b,c,x), I have a data vector of x and a vectory y of realized value of f. Case1 I tried to estimate c with (a=0.3, b=0.5) fixed: nls(y~f(a,b,c,x), control=list(maxiter = 100000, minFactor=0.5 ^2048),start=list(c=0.5)). The error message is: "number of iterations exceeded maximum of

Hello, I am running a simple nls model (which a friend ran OK) but I get the following error: Error in nls(y ~ R * (1 - (x/K)^2), data = nls.dat, start = list(R = 0.3, : object 'R_nls_iter' not found Does anyone know what the 'R_nls_iter' error is? The data are: x=1:8 ; y=c(14,19,25,34,43,56,69,76) # starting values: R=.3, K=94 Thanks in advance. Jeff

Dear list, I have encountered a problem with predict.nls (Windows XP, R.2.5.0), but I am not sure if it is a bug... On the nls man page, an example is: DNase1 <- subset(DNase, Run == 1) fm2DNase1 <- nls(density ~ 1/(1 + exp((xmid - log(conc))/scal)), data = DNase1, start = list(xmid = 0, scal = 1)) alg = "plinear", trace =

Hi all, I need to use the parameter estimates of nls() for further analysis. I know how to do in S+, e.g. nls(...)$parameters. In R, the attributes(nls(...)) does not have parameters, how would one get the parameter values out of nls()? Thanks in advance. Nancy

I want to fit the model y=a*x^b using nls; where "a" should be different for each level of a factor. What is the easiest way to fit it? Can i do it with nls? I've looked the help pages and the MASS example in page 249 but the formula is different and I don't know how to specify it for my model. Thanks, Manuel [[alternative HTML version deleted]]

We would like to fit parameters using a simulation with stochastic processes as theoretical values. We generate a simple exemple with nls.lm to see the logic and the problem: First without stochasticity (it is a dummy example, the fited value is simple the mean of a set of 10 numbers): #Ten numbers x <- 1:10 #Generate 10 Gaussian random number with mean=3 sd=1 simy <- rnorm(length(x),

logLik.nls does not count the df's correct. I get df=1 although I fit a probit-model with 3 parameters. Example: x <- c(-2.3, -2.0, -1.3, -1.0, -0.7, -0.3, 0.0, 0.3) y <- c(80, 80, 54, 43, 24, 18, 12, 12) fit.nls <- nls(y ~ diff * pnorm(beta * (x - alpha)), start=c(alpha=-1, beta=-1, diff=100)) logLik.nls(fit.nls) # `log Lik.' -21.43369 (df=1) Sincerely

Hello everyone, I'm trying to test the accurracy of R on the Eckerle4 dataset from NIST and I don't understand how the control option of the nls function works. I tought nls(...) was equivalent to nls(...control=nls.control()) i.e nls.control() was the default value of control, but here is the error I get : > n2=nls(V1~(b1/b2) *

I'm running into problems trying to use the nls function to fit the some data. I'm invoking nls using nls(s~k/(a+r)^b, start=list(k=1, a=13, b=0.59)) but I get errors indicating that the step has been reduced below the minimum step size or an inifinity is generated in numericDeriv. I've tried to use a variety of starting values for a, b, k but get similar errors. Is there

Hi, I was trying to run the example of Indomethacin kinetics from the book: ## From Pinheiro/Bates, Mixed-Effects-Models in S and S-Plus, ## Springer, Second Printing 2001, Section 6.2 library(nlme) plot(Indometh) fm1Indom.nls <- nls(conc~SSbiexp(time,A1,lrc1,A2,lrc2), data=Indometh) summary(fm1Indom.nls) plot(fm1Indom.nls,Subject~resid(.),abline=0) ## .... the last plot command gives me the

HI, i have some prob when i try to use nls(). my data is 1D vector, I tried to use a polynomial function(order is 3) to fit it. the data series is stored in x. the a0, a1, a2, a3 below is coefficient, which i hope i can get from calls "nls" > z <- nls( ~ a0 + a1 * x + a2 * x * x + a3 * x * x * x, data = x ) Error in match.call(definition, call, expand.dots) : .Primitive... is