similar to: nls.lm & AIC

Dear R useRs, I have a problem with nls.lm function of minpackl.lm package. I need to fit the Van Genuchten Model to a set of data of Theta and hydraulic conductivity with nls.lm function of minpack.lm package. For the first fit, the parameter estimates keep changing even after 1000 iterations (Th) and I have a following error message for fit of hydraulic conductivity (k); Reason for

Hello, We previously had Win2008 R2 DCs which we have begun to replace with Win2012 servers (forest is still at 2008 level however). I was able to query DFS via rpcclient but now I find that I am unable to. I know that SMB3 was introduced in Win2012 but I believe that it should auto-negotiate earlier versions. I did however test from v4.1.9 as well, unfortunately that still fails. From Samba3

Dear Geskus, I want to develop a prediction model. I followed your paper and analysed thro' weighted coxph approach. I can develop nomogram based on the final model also. But I do not know how to do internal validation of the model and subsequently obtain calibration plot. Is it possible to use Wolbers et al Epid 2009 approach 9 (R code for internal validation and calibration) . It is

Dear Thomas, I want to use evaluate effect of Age using restricted cubic form in the FGR function as Fgr.crr <- FGR(Hist(time, event) ~ rcs(Age_years), data=dat) It provides error. " Error in parse(text = termtext, keep.source = FALSE): .... 1: response ~ rcs(Age_years Do I need to change any of the R code? Regards Amalraj Raja The University of Aberdeen is a charity

Dear All, I would like to use R function 'selectFGR' of fine gray model in competing risks model. I used the 'Melanoma' data in 'riskRegression' package. Some of the variables are factor. I get solution for full model but not in variable selection model. Any advice how to use factor variable in 'selectFGR' function. The following R code is produced below

Hi, I am new to R and I want to export data into Stata. Could somebody help with that? Thanks a lot. This is the code I am using: > setwd("D:/datasets/Seg-bcn/ESBD") > data1 <- readRDS("r17045_ESDB_Habitatges_BDD_V_1_0.rds") > library(foreign) > write.dta(data="data1", file = "D:/datasets/data1.dta") Error in write.dta(data =

Hi , library(foreign) write.dta(data1, "data1.dta") should work. The file will be saved in the working directory. Use getwd() to know the working directory. Best wishes Amalraj Raja -----Original Message----- From: R-help [mailto:r-help-bounces at r-project.org] On Behalf Of rosario scandurra Sent: 22 March 2018 07:47 To: r-help at r-project.org Subject: [R] exporting data to stata

On Thu, Mar 22, 2018 at 4:52 AM, Raja, Dr. Edwin Amalraj <amalraj.raja at abdn.ac.uk> wrote: > Hi , > > library(foreign) > write.dta(data1, "data1.dta") > > should work. I don't think so: > library(foreign) > example(svydesign) > write.dta(dstrat, "~/Downloads/foo.dta") Error in write.dta(dstrat, "~/Downloads/foo.dta") : The

I'm wondering whether AIC scores extracted from nls() objects using AIC() are based on the correct number of estimated parameters. Using the example under nls() documentation: > data( DNase ) > DNase1 <- DNase[ DNase$Run == 1, ] > ## using a selfStart model > fm1DNase1 <- nls( density ~ SSlogis( log(conc), Asym, xmid, scal ), DNase1 ) Using AIC() function: >

Hello, I am currently trying to show the abundance of two species of zooplankton within the North Sea as pie chart bubble plots. I followed Werner Wernersen's advice in R help (http://finzi.psych.upenn.edu/R/Rhelp02a/archive/48644.html) and used Paul Murrell's paper "Integrating Grid Graphics Output with Base Graphics Output" (in R News) to try and do this (using the gridBase

I am trying to install minpack.lm on R 3.3.3 (Debian version) on a Chromebook. But I get this error: ``` > install.packages("minpack.lm") Installing package into ?/home/marongiuluigi/R/x86_64-pc-linux-gnu-library/3.3? (as ?lib? is unspecified) trying URL 'https://cran.rstudio.com/src/contrib/minpack.lm_1.2-1.tar.gz' Content type 'application/x-gzip' length 43029 bytes

Hi I am using Ubuntu 8.04 64 bit, R as below, Matlab 7.6.0. I would like to transfer mat files back and forward between R and Matlab. Whilst I have used Matlab for years its been a long time since I have used R (hence question may be a bit simple) Running code A <- c(1:10) dim(A) <- c(2,5) library(R.matlab) writeMat('A.mat', A=A) Does not appear to generate any mat file

Thank you, it looks like I have already libisl: ``` apt search libisl Sorting... Done Full Text Search... Done libisl-dbg/oldstable 0.18-1 amd64 manipulating sets and relations of integer points bounded by linear constraints libisl-dev/oldstable 0.18-1 amd64 manipulating sets and relations of integer points bounded by linear constraints libisl15/oldstable,now 0.18-1 amd64

I don't know about the configuration. I installed R using the standard protocol for Chromebook http://blog.sellorm.com/2018/12/20/installing-r-and-rstudio-on-a-chromebook/ the rest, it was done by the system itself... On Tue, Jul 14, 2020 at 1:30 PM Dirk Eddelbuettel <edd at debian.org> wrote: > > > There is something wrong with your system / setup I did not notice first: >

Dear R users, I have a problem. I would like to solve the following: I have pL = 1/(1+e^(-b0+b1)) pM = 1/(1+e^(-b0)) pH = 1/(1+e^(-b0-b1)) My target function is TF= mean(pL,pM,pH) which must equal 0.5% My non-linear constraint is nl.Const = 1-(pM/pH), which must equal 20%, and would like the values of both b0 and b1 where these conditions are met. I have searched widely for an answer,

All - I have data: TL age 388 4 418 4 438 4 428 5 539 10 432 4 444 7 421 4 438 4 419 4 463 6 423 4 ... [truncated] and I'm trying to fit a simple Von Bertalanffy growth curve with program: #Creates a Von Bertalanffy growth model VonB=nls(TL~Linf*(1-exp(-k*(age-t0))), data=box5.4, start=list(Linf=1000, k=0.1, t0=0.1), trace=TRUE) #Scatterplot of the data plot(TL~age, data=box5.4,

Hi all, I'm having trouble with the model generating 'dredge' function in the MuMIn 'Multi-model Inference' package. Here's the script: globalmodel<- glm(TB~lat+protocol+tested+ streams+goats+hay+cattle+deer, family="binomial") chat<- deviance(globalmodel)/59 #There we 59 residual degrees of freedom in this global model. models<- dredge(globalmodel,

Dear All, In the past I have often used minpack (http://bit.ly/zXVls3) relying on the Levenberg-Marquardt algorithm to perform non-linear fittings. However, I have always dealt with a function of a single variable. Is there any difference if the function depends on two variables? To fix the ideas, please consider the function f(R,N)=(a/(log(2*N))+b)*R+c*N^d, where a,b,c,d are fit parameters. For

I am looking into fitting a so-called double von Bertalanffy function to fish length-at-age data. Attempting to simplify the situation, the model looks like this ... Y ~ f(X; a,b,c) if x < Z Y ~ g(X; a,d,e) if x >= Z where * f and g are non-linear functions (the "traditional" "single" von Bertalanffy growth function), * Y (length) and X (age) are observed variables,

? Mon, 6 Nov 2023 17:53:49 +0100 Troels Ring <tring at gvdnet.dk> ?????: > Hence I wonder if I could somehow have non linear regression to find > the 3 pK values. Below is HEPESFUNC which delivers charge in the > fluid for known pKs, HEPTOT and SID. Is it possible to have > root-finding in the formula with nls? Sure. Just reformulate the problem in terms of a function that