similar to: Problem comparing Akaike's AIC - nlme package

R Users, I am new to R and have tried to figure out how to automate this process instead of using excel. I have read in this dataframe into r with read.table. I need to reshape the data from the first table into the format of the second table. TractID StandID Species CruiseDate DBHClass TreesPerAcre Carbon Stand 1 Loblolly Pine 5/20/2010 10 1.2 Carbon Stand 1 Loblolly Pine

Hallo! I want to plot multiple grouped data in a postscript file using a loop. As I use a loop no plot (or just one empty plot) is generated. Here an example: library(nlme) data(Loblolly) # example data from nlme postscript("PSFile.ps") for (i in 1:1) # just as example { plot(Loblolly) } dev.off() Result: Just an empty PSFile.ps. (Withoput the loop it works. May anybody help? Karl

Hi all, I have a pretty basic question about categorical variables but I can't seem to be able to find answer so I am hoping someone here can help. I found that if the factor names are all in numbers, fitting the model in lm would return labels that are not very recognizable. # Example: let's just assume that we want to fit this model fit <- lm(height ~ age + Seed,

I ran into a problem trying to make a plot from a file that's read using source. Basically, I have the following code in a file "plot.R" : library(nlme) data(Loblolly) fm1 <- nlme(height ~ SSasymp(age, Asym, R0, lrc), data = Loblolly, fixed = Asym + R0 + lrc ~ 1, random = Asym ~ 1, start = c(Asym = 103, R0 = -8.5, lrc = -3.3))

Hello, How do I specify the formula and random effects without a startup object ? I thought it would be a mixture of nls and lme. after trying very hard, I ask for help on using nlme. Can someone hint me to some examples? I constructed a try using the example from nls: #variables are density, conc and Run #all works fine with nls DNase1 <- subset(DNase, Run == 1 ) fm2DNase1 <- nls(

I have a need to call and pass arguments to nlme() from within another function. I use R version 1.8. I have found an apparent way to make this work, but I would appreciate some comments on whether this fix is really appropriate, or there is another way to do it that does not involve changing the source code. I don't have enough experience to start changing the sorurce code of a library

Hello, first of all I have found lots of different versions of the FPE which have given me different results. I was wondering if there was an explicit command in R to compute the FPE of a model. Thank you in advance, Jonny -- View this message in context: http://r.789695.n4.nabble.com/Akaike-s-Final-Prediction-Error-FPE-tp4519011p4519011.html Sent from the R help mailing list archive at

can you recommend a good manual for R that starts with a data set and gives demonstrations on what can be done using R? I downloadedR Langauage definition and An introduction to R but haven't found them overly useful. I'd really like to be able to follow some tutorials using a dataset or many datasets. The datasets I have available on R are Data sets in package 'datasets':

Hello all, i hope you don't mind my off topic question. i want to use the Akaike criterion for variable selection in a regression model. Does anyone know some basic literature about that topic? Especially I'm interested in answers to the following questions: 1. Has (and if so how has) the criterion to be modified, if i estimate the transformations of the variables too? 2. How is the

Dear all I try to refine my nlme models and with partial success. The model is refined and fitted (using Pinheiro/Bates book as a tutorial) but when I try to plot plot(augPred(fit4)) I obtain Error in predict.nlme(object, value[1:(nrow(value)/nL), , drop = FALSE], : Levels (0,3.5],(3.5,5],(5,7],(7,Inf] not allowed for vykon.fac > Is it due to the fact that I have unbalanced

Hola a todos Les consulto por un problema con xtable y nlme, tomando un ejemplo del manual de nlme para obtener los resultados en latex utilizando xtable, se puede utilizar el siguiente código, pero hay un problema y causa error. library(nlme) library(xtable) fm1 <- nlme(height ~ SSasymp(age, Asym, R0, lrc), data = Loblolly, fixed = Asym + R0 + lrc ~ 1,

Hey, i have a question about how to reorganize a data frame in the easiest way. my example: what would be the easiest way to bring a data.frame such like this: ---- nr height age Seed 1 1 4.51 3 301 2 15 10.89 5 301 3 29 28.72 10 301 4 43 41.74 15 301 5 57 52.70 20 301 6 71 60.92 25 301 7 2 4.55 3 303 8 16 10.92 5 303 9 30 29.07 10 303 10 44

Dear list members, I am working with a multilevel growth curve, that in its simplest form goes like follows: Yit = Ai + Bi t + eit (the error term is assumed to follow an AR(1) autorregressive process) One major topic in my research is the convergence in the values of Y over time. Thus, I am interested in the relationship between the random effects for the intercept and the slope, and I

Am Dienstag, 25. April 2017, 08:50:34 schrieb Dirk Eddelbuettel: > On 25 April 2017 at 14:58, G?ran Brostr?m wrote: > | hello, > | > | I just installed R-3.4.0 from scratch: > | > | $ sudo apt install r-base > | > | but when I try > | > | > library(survival, lib.loc = "/usr/lib/R/library") > | > fit <- coxph(Surv(exit, event) ~ x, data =

Hello all. I have been working on a (fairly simple) function for way too long. I’ve really hit a wall and I was hoping someone might be able to point me in the right direction. I have (attempted) to create a function that has an embedded while loop. The while loop works fine by itself, however, when the while loop is embedded in the function, the function fails. I’m not sure why this

I need your help to make R works on my linux box, runing fedora 11. Few things on the machine and steps I did: 1. uname -a shows: Linux bagvapp 2.6.29.4-167.fc11.i586 #1 SMP Wed May 27 17:14:37 EDT 2009 i686 athlon i386 GNU/Linux 2. it has a gcc (version 4.4) RedHat's build 3. the g77 comes with the box does not work (R's configure tells it could not compile simple fortran code); so

Am Dienstag, 25. April 2017, 11:21:31 schrieb Dirk Eddelbuettel: > On 25 April 2017 at 16:11, Johannes Ranke wrote: > | This looks similar to what I got this morning when I tested my > | (unreleased) > | backport of R 3.4.0 to Debian jessie. My test was > | > | library(MASS) > | example(rlm) > | > | and there was an object that was not found. I am on a train on the way

Dear all, does anyone have r code to perform model-averaging of regression parameters by Akaike weights, and/or to do all-possible-subsets lm modelling that reports parameter estimates, AICc and number of parameters for each model? I have been looking for these in the archive but found none. (I am aware that many of you would warn me against these methods advocated by Burnham and Anderson

I am using lm simulation in R and try to find the AICc and Akaike weight of the model. I searched out that using package "AICcmodavg" AICc is easily to get. I wonder how can I get the "Akaike weight", any function I can use to generate it? Thanks in advance. Sunny [[alternative HTML version deleted]]

Please can you help me I have the following problem: I have selected an lm model through the step procedure which visualize for each step the AIC value; then I have calculated for the initial model and the selected one the AIC using the funnction AIC. The results are different.What's happened? Emilia Rocco Dipartimento di Statistica "G. Parenti" Università di Firenze e-mail: