similar to: A simple question regarding plot of nls objects

Hi there, I'm quite new to R (and statistics), and I like it (both)! But I'm a bit lost in all these packages, so could someone please give me a hint whether there exists a package for fitting exponential curves (of the type t --> \sum_i a_i \exp( - b_i t)) on a noisy signal? In fact monoexponential decay + polynomial growth is what I'd like to try. Thanks in advance,

DeaR I am trying to use a dynamically create formula with nlsList and nlme, but I cannot get the environment of the string-generated formal to work similarly to the manually entered one. Any idea? Dieter #----- library(nlme) # Pinheiro/Bates p 280 fm1Indom.lis = nlsList(conc~SSbiexp(time,A1,lrc1,A2,lrc2), data=Indometh) nlme(fm1Indom.lis,random=pdDiag(A1+lrc1+A2~1)) # works... # Simulating

Hello all! I have a problem to use a biexponential regression model: I use this code: n3<-nls(proc~SSbiexp(cls,a,b,c,d),data=bline) and this is the error message: Error in nls(y ~ cbind(exp(-exp(lrc1) * x), exp(-exp(lrc2) * x)), data = xy, : singular gradient My data is like this: structure(list(proc = c(387.177462830167, 508.090511433077, 321.836817656365, 151.226805860727,

Following the Indomethicin example in Pinheiro & Bates, chapter 6, page 277 etc, coming to the following comand: fm2Indom.nlme <- update( fm1Indom.nlme, random = pdDiag(A1 + lrc1 + A2 ~ 1) ) debugging nlme gives the following output: Browse[1]> n debug: modelResid <- ~eval(model, data.frame(data, getParsNlme(plist, fmap, rmapRel, bmap, groups, beta, bvec, b, level,

I can''t get my view to display the most recent parameters from an associated object in a view... here is a birds-eye of my app: I have two models, Ferms and Kinetics. Ferm has_many :kinetics, Kinetic belongs_to :ferm. Kinetic has the fields ferm_id, brix and temp. In my ferms/index view I have a table listing the attributes of each ferm instance. I would like to display the most recent

R users, I intention is to calculate some summary statistics across factor levels. I know that in Hmisc package there is a summary function which produces neat summary statistics when using "cross" option. I would like to produce similar output with N and Missing columns but produce a data.frame. Is there any built-in function for that? #example data install.packages("Hmisc")

Full_Name: Kevin Wright Version: 1.4 OS: Windows 95 Submission from: (NULL) (170.54.59.160) Note: This was the 1.4 build for Windows that Brian Ripley made available. The first example in the help for reshape doesn't work for me. When I cut and paste, this is what happens: > data(Indometh,package="nls") > summary(Indometh) Subject time conc

Given a data frame of a categorical variable and two continuous variables, I would like to display one continuous variable against the other for each value of the categorical variable, all superimposed on the same plot. For example: data(Indometh); str(Indometh) Classes 'nfnGroupedData', 'nfGroupedData', 'groupedData' and 'data.frame': 66 obs. of 3

I have dose response data analyzed with the package 'drc'. 'summary(mymodel)' prints my kinetic parameters. I want that text in an ASCII text file. I want to get exactly what I would get if I copied and pasted from the terminal window. I've read the documentation on data export to text files here:

Hi All, I am currently preparing some form of slideshow introducing R and its capabilities for some colleagues. The thing will be about 30 mins, and I'd like to have some "pretty pictures" and some "amazing facts" (I'm trying to sell, obviously :)). Can I ask if it's possible to easily retrieve a gross figure of the number of functions in R considering the

*Respected Sir, I have a simple question regarding plots of time series in R. I have to plot "conc" against "time" **for each individual and display in the same panel for the in-built dataset "Indometh" in R. * ***I have six time series, say subject1.ts, subject2.ts, ............., subject6.ts. The observations are taken at an interval of 0.25 hr. All of the series

?sink On May 18, 2018 9:47:25 AM PDT, Ed Siefker <ebs15242 at gmail.com> wrote: >I have dose response data analyzed with the package 'drc'. >'summary(mymodel)' prints my kinetic parameters. I want >that text in an ASCII text file. I want to get exactly what I >would get if I copied and pasted from the terminal window. > >I've read the documentation on

Hi all, I have a matrix of 474 rows (samples) with 565 columns (variables). each of the 474 samples belong to one of 120 groups, with the groupings as a column in the above matrix. For example, the group column would be: 1 1 1 2 2 2 . . . 120 120 I want to randomly select one from each group. Not all the groups have the same number of samples, some have 4, some 3 etc. Is there a function to

Hi, It's probably a simple issue but I'm struggling with that. I'll use the example shown in the help page. head(Indometh) wide <- reshape(Indometh, v.names="conc", idvar="Subject", timevar="time", direction="wide") head(wide) reshape(wide, idvar="Subject", varying=list(2:12), v.names="conc",

At the top of page 283 of Pinheiro and Bates, a covariance structure for the indomethicin example is specified as random = pdDiag(A1 + lrc1 + A2 + lrc2 ~ 1) The argument to pdDiag() looks like a two-sided formula, and I'm struggling to reconcile this with the syntax described in Ch4 of the book and online. Further down page 283 the formula is translated into list(A1 ~ 1, lrc1 ~ 1, A2 ~ 1,

Dear R-listers, I would like to know if there is a way to programmatically generate parameter start values for the model y~(a*exp(b*x)+c*exp(d*x)) in R. I've scoured the help files and archives for nls() and similar searches, and have read Fox 2002 - the best advice has been to make estimates from a priori knowledge of the data. However, in the Matlab CurveFit tool, reliable start values are

I try to fit reaction kinetic data to a given hypothetical model consisting of 3 ODEs. After some reading in Bates/Watts and the literature cited there (e.g. Jennrich/Bright) I looked in R for functions that support the use of the matrix exponential method. Until now I used for a similar (but simpler) problem the nls package and fitted against the the parameterized solution function. But this

Dear R users, I don't know how to compute an exponential model like this: proc=a*exp(b*cls), or proc=a*exp(b*cls)+c*exp(d*cls). Please help me to solve this problem! Thank you! My data is: row.names proc cls 1 0.5 452.616206 0.5 2 1 255.864021 1.0 3 1.5 150.885316 1.5 4 2 86.289600 2.0 5 2.5 56.321559 2.5 6 3 39.504444 3.0 7 3.5 25.570308 3.5 8 4 5.382726 4.0 -- --- Catalin-Constantin

Hello R list, This is a question for anyone who has used the by() command. I would like to perform a regression on a data frame by several factors. Using by() I think that I have able to perform this using the following: > lm.r <- by(master, list(Sectionf=Sectionf, startd=startd), function(x) lm (tot.c ~ starttime, data = x)) So that is, I would like to perform separate regressions for

Hello! I would like to know if R can solve Differential Equations... I don't think so because, in my point, I see R like a Statistical System, not a Math System. Am I wrong? Thank you very much. M??rcio de Medeiros Ribeiro Graduando em Ci??ncia da Computa????o Departamento de Tecnologia da Informa????o - TCI Universidade Federal de Alagoas - UFAL Macei?? - Alagoas - Brasil Projeto CoCADa