similar to: Problems with nls

The problem is badly scaled -- parameters from very small to very big. nlmrt package manages a bit better, but scaling would likely make it and nls both happier. nlxb insists on having its data in a data frame. Here's my code rm(list=ls()) Laptop_sale <- c(1405, 1863,2027,2669,2938,5275,6595,6943,8621,10905,12420,22400,32380,31600,34900,43163,47838,47592) CuSale <- Laptop_sale time

Hi All. I've run into a problem with the plinear algorithm in nls that is confusing me. Assume the following reaction time data over 15 trials for a single unit. Trials are coded from 0-14 so that the intercept represents reaction time in the first trial. trl RT 0 1132.0 1 630.5 2 1371.5 3 704.0 4 488.5 5 575.5 6 613.0 7 824.5 8 509.0 9

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

Dear R gurus, As part of finding initial values for a much more complicated fit I want to fit a function of the form y ~ a + bx + cx^d to fairly "noisy" data and have hit some problems. To demonstrate the specific R-related problem, here is an idealised data set, smaller and better fitting than reality: # idealised data set aDF <- data.frame( x= c(1.80, 9.27, 6.48, 2.61, 9.86,

Hi, Is there available package on the optimization function using Newton-Raphson method (iterative quadratic approximation)? I have been using the 'optim' function in R and found it really unstable (it depends heavily on the initial values and functional forms). If I have to code it by myself, can I get some advice on how to start (any good reference or sample code)? I really

hello all i havnt had a chance to read through the references provided for the "nls" function (since the libraries are closed now). can anyone shed some light on how the "plinear" algorithm works? also, how are the fitted values obtained? also, WHAT DOES THE ".lin" below REPRESENT? thanking you in advance ###################################### i have a quick

I have found some "issues" (bugs?) with nls confidence intervals ... some with the relatively new "port" algorithm, others more general (but possibly in the "well, don't do that" category). I have corresponded some with Prof. Ripley about them, but I thought I would just report how far I've gotten in case anyone else has thoughts. (I'm finding the code

can anyone tell me how can i control the method of estimation (i.e. scoring method or Newton raphson method) in glm and compute deviance function ? -- View this message in context: http://r.789695.n4.nabble.com/changing-method-of-estimation-in-GLM-tp3170836p3170836.html Sent from the R help mailing list archive at Nabble.com.

Hi everyone, I'm trying to perform a bi exponential Fit with the package NLS. the plinear algorithm seems to be a good choice see: p<-3000 q<-1000 a<--0.03 b<--0.02 t<-seq(0:144);t y<-p*exp(a*t) + q*exp(b*t)+rnorm(t,sd=0.3*(p* exp(a*t) + q*exp(b*t))) fittA <- nls(y~cbind(exp(a*t), exp(b*t)), algorithm="plinear",start=list(a=-.1, b=-0.2), data=list(y=y, t=t),

Hello, Does anyone know whether the gls function in the nlme library uses the Newton-Raphson or EM algorithm to find the restricted log-likelihood or maximum log-likelihood estimates? Brendan Klick bklick@jhsph.edu [[alternative HTML version deleted]]

Hi, Does anyone know if there is a function to find the maximum likelihood estimates of glm using Newton Raphson metodology instead of using IWLS. Thanks Valeska Andreozzi -------------------------------------------------------- Department of Epidemiology and Quantitative Methods FIOCRUZ - National School of Public Health Tel: (55) 21 2598 2872 Rio de Janeiro - Brazil

I have not included the previous postings because they came out very strangely on my mail reader. However, the question concerned the choice of minimizer for the zeroinfl() function, which apparently allows any of the current 6 methods of optim() for this purpose. The original poster wanted to use Newton-Raphson. Newton-Raphson (or just Newton for simplicity) is commonly thought to be the

I'm trying to fit a function y=k*l^(m*x) to some data points, with reasonable starting value estimates (I think). I keep getting "singular matrix 'a' in solve". This is the code: ox <- c(-600,-300,-200,1,100,200) ir <- c(1,2.5,4,9,14,20) model <- nls(ir ~ k*l^(m*ox),start=list(k=10,l=3,m=0.004),algorithm="plinear") summary(model) plot(ox,ir) testox <-

Dear all i want to estimated the parameter of the gamma density(a,b,d) f(x) = (1/gamma(b)*(a^b)) * ((x-d)^(b-1)) * exp{-(x-d)/a)} for x>d f(x) = Age specific fertility rate x = age when i run this in R by usling nls() gamma.asfr <- formula(asfr ~ (((age-d)^(b-1))/((gamma(b))*(a^b)))* exp(-((age-d)/a))) gamma.asfr1 <- nls(gamma.asfr, data= asfr.aus, start = list(b = 28, a = 1, d= 0.5),

Hi, df <- read.table("data.txt", header=T); library(nls); fm <- nls(y ~ a*(x+d)^(-b), df, start=list(a=max(df->y,na.rm=T)/2,b=1,d=0)); I was using the following routine which was giving Singular Gradient, Error in numericDeriv(form[[3]], names(ind), env) : Missing value or an Infinity produced when evaluating the model errors. I also tried the

Hi, Could anyone tell me what is the command used in R to do 1. Differentiation 2. Newton Raphson method (Numerical Analysis in general...) Are there any packages separately for this? Thanks for your help! BR, Shubha [[alternative HTML version deleted]]

Hi , I am trying to get some estimator based on lognormal distribution when we have left,interval, and right censored data. Since, there is now avalible pakage in R can help me in this, I had to write my own code using Newton Raphson method which requires first and second derivative of log likelihood but my problem after runing the code is the estimators were too high. with this email ,I provide

I'm a bass player, I admit it. I came across a number of people talking about bass response with Ogg Vorbis and it piqued my interest, I live for this stuff. I am using the Ogg files to distribute songs as converted right from the 32 bit masters. This is a much different thing than ripping a 16 bit CD audio file that has been mushed and compressed much before it winds up as an Ogg file. When

Dear all, I want to solve a score function by using Newton-Raphson algorithm. Is there such a fucntion in R? I know there's one called optim, but it seems only doing minimizing or maximizing. Thanks, Jimmy

Hi, I am trying to get the maximum likelihood estimator for lognormal distribution with censored data;when we have left, interval and right censord. I built my code in R, by writing the deriving of log likelihood function and using newton raphson method but my estimators were too high " overestimation", where the values exceed the 1000 in some runing of my code. is there any one can