similar to: NLS-Support

Hello. It's a thing which all Russia and, I think, many other countries need. Patch allow you to specify smb server and local IO charsets. Two new options added to smbmount: iocharset=<charset> and servercharset=<charset>. They'll passed to kernel and proc.c module makes NLS conversion if need. Patches in attachment. -------------- next part -------------- A non-text

Howdee, My question appears at #6 below: 1. I want to model the growth of each of a large number of individuals using a 4-parameter logistic growth curve. 2. nlme does not converge with the random structure that I want to use. 3. nlsList does not converge for some individuals. 4. I decided to go around nlsList using: t(sapply(split(data, list(data$id)), function(subd){coef(nls(mass ~

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),

Hello, I am attempting to fit a non-linear model (Von Bertalanffy growth model) to fish length-at-age data with the purpose of determining if any of the three parameters differ between male and female fish. I believe that I can successfully accomplish this goal assuming an additive error structure (illustrated in section 1 below). My trouble begins when I attempt this analysis using a model

Dear list, I'm trying to learn how to use nlme to be able to fit ad analyse mixed-model logistic regressions. In order to keep things simple, I started by the simplest possible model : a one (fixed-effect ...) continuous variable. This problem is, of course, solved by glm, but I wanted to look at a "hand-made" nls fit, in order to be able to "generalize" to nlme

Hello I have updated my version of how to get "nls" working in smbfs for the changes made in the 2.2.16pre2 Linux kernel (both nls and smbfs). It is now a bit smaller and perhaps cleaner (except for the CONFIG_SMB_NLS, that could be removed, and the nls_utf8 abuse :) Also, it now uses an ioctl to set the codepages to use (borrowed from the work by Artem V. Ryabov). This allows you to

Dear R community, I have currently some problems with non linear regression analysis in R. My data correspond to the degradation kinetic of a pollutant in two different soil A and B, x data are time in day and y data are pollutant concentration in soil. In a first time, I want to fit the data for the soil A by using the Ct = C0*exp(-k*Tpst) with Ct the concentration of pollutant at time t, C0

Hello, i have a problem with the function nls(). This are my data in "k": V1 V2 [1,] 0 0.367 [2,] 85 0.296 [3,] 122 0.260 [4,] 192 0.244 [5,] 275 0.175 [6,] 421 0.140 [7,] 603 0.093 [8,] 831 0.068 [9,] 1140 0.043 With the nls()-function i want to fit following formula whereas a,b, and c are variables: y~1/(a*x^2+b*x+c) With the standardalgorithm

Hi all, I'm struggling with nls. How do you know if your model is significant? For a lm, you get a p-value, but you don't get it for a nls. Is there a way to calculate it? For a lm I use this: a<-summary(lm(model ~obs)) f.stat<-a$fstatistic p.value<-1-pf(f.stat["value"],f.stat["numdf"],f.stat["dendf"]) Is there something similar for a nls?

Hi all I?ve got a problem using boxcox.nls function in nlrwr packagge. I?m fitting several non linear models to these data: > 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 I used nls function with self

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, does Samba use localhost as WINS-Server, if only wins support = yes is set? Regards, Marc Hansen

Hi, my log is full with etries like this: Unable to load NLS charset utf-8 utf8 support is build into the kernel and selected as default nls page. testparm /etc/samba/smb.conf -v|grep charset : dos charset = CP850 unix charset = UTF8 display charset = UTF8 so whats wrong? regards julius

Hi, I've been trying to work with the gnls() function in the "nlme" package. My decision to use gnls() was so that I could fit varPower and such to some of the data. However, in working with a small dataset, I've found that the results given by gnls() don't seem to make any sense and they differ substantially from those produced by nls(). I suspect that I am just

I'm using Urban Widmark's smbfs/Linux kernel patch (2.2.14) to display iso-8859-1 characters in file names on NT mounts. The patch works fine for me; I'm only wondering if and when it will be integrated into the Linux kernel. After all, NLS is an essential feature and not just nice-to-have for all non-anglophone users... Yes, I know this is a bit off-topic on this list, but there

Dear all, I noticed the following under R 1.8.1 (when nls was still a separate package) but the same problem occurs under R 1.9.0 (where most (all?) of nls is now in the stats package): > data(Puromycin) > fm <- nls(rate~SSmicmen(conc,b0,b1), Puromycin, subset = state=="treated") > coef(summary(fm)) NULL The problem seems to be that summary.nls uses the name

Hello there I have the following model based on the hollings disc equation for the type II functional response for 2 data sets: nls(eaten~(a*suppl)/(1+a*h*suppl) where eaten is the number of prey eaten by a predator and suppl is the number of prey initially supplied to the same predator. I have parameter estimates of 'a' and 'h' for the two populations studied and would like

?tryCatch -- Sent from my phone. Please excuse my brevity. On October 20, 2017 7:37:12 AM PDT, Evangelina Viotto <evangelinaviotto at gmail.com> wrote: >Hello I?m need fitt growth curve with data length-age. I want to >evaluate >which is the function that best predicts my data, to do so I compare >the >Akaikes of different models. I'm now need to evaluate if changing the

Dear R users, I am new in R and I want to use the nls package to analyze some experimental data. The data is in the attached file "data". It is the response "Sav" measured at different "C0". Basically, the "C0" is a function of C1, K2, and r, and the "Sav" is a function of C0, C1, K2, and r. The math equations are shown in the attached

Hi all, I'm trying to do a simple curve fit and coming up with some interesting results I would like to get comment on. So as shown below, tsR is my explanatory and response is... well... my response. This same data in gnumeric gets fitted with the curve "response=10078.4 + 1358.67 * ln (explanatory - 2009.07) So I'm using nls with the start values supplied by gnumeric. in