similar to: regression with more than one observation per x value

Dear all, Is there a way to retrieve standard errors from nls models? The help page tells me that arguments such as se.fit are ignored... Many thanks and best wishes Christoph -- Dr. rer.nat. Christoph Scherber University of Goettingen DNPW, Agroecology Waldweg 26 D-37073 Goettingen Germany phone +49 (0)551 39 8807 fax +49 (0)551 39 8806 Homepage http://www.gwdg.de/~cscherb1

Dear R users, I am currently analyzing a dataset using lme(). The model I use has the following structure: model<-lme(response~Covariate+TreatmentA+TreatmentB,random=~1|Block/Plot,method="ML") When I plot the residuals against the fitted values, I see a clear positive trend (meaning that the variance increases with the mean). I tried to solve this issue using weights=varPower(),

Dear all, For an introductory course on glm?s I would like to create an example to show the difference between glm and transformation of the response. For this, I tried to create a dataset where the variance increases with the mean (as is the case in many ecological datasets): poissondata=data.frame( response=rpois(40,1:40), explanatory=1:40) attach(poissondata) However, I have run into

Dear R users, Assume I have three models with the following AIC values: model AIC df model1 -10 2 model2 -12 5 model3 -11 2 Obviously, model2 would be preferred, but it "wastes" 5 df compared to the other models. Would it be allowed to select model3 instead, simply because it uses up less df and the delta-AIC between model2 and model3 is just 1? Many thanks for any

Dear all, I have a data frame that looks like this: c1 c2 c3 A B C B C A A A B and so on; I?d like to produce one single vector consisting of the columns c1,c2, c3, such that vector=("A","B","A","B","C","A","C","A","B") I guess it?s easy to do but I don?t know how...Can anyone

Dear R users, I??ve got a simple question but somehow I can??t find the solution: I have a data frame with columns 1-5 containing one set of integer values, and columns 6-10 containing another set of integer values. Columns 6-10 contain NA??s at some places. I now want to calculate (1) the number of values in each row of columns 6-10 that were NA??s (2) the sum of all values on columns 1-5

Dear R users, Using xyplot(), how can I position the key in the *margin* outside the plotting area ? My problem is that the key always overlaps with the x axis labels, no matter how I try to specify any of the par() arguments (e.g. oma()). Many thanks for any suggestions! Christoph ### for information, here??s the code I use par(oma=c(0,0,3,0)) ###this, I think, is what should be changed

I wanted a function that would give the euclidean distance of a vector. Then I was happy, because I found vecnorm listed on pg 55 of V&R (3rd edn) which I had just bought today. Then I was sad, because R did not have vecnorm. Then I was happy again, because I bethought myself that I could copy the function vecnorm from splus to my code. Then I was sad again because R complained >

Dear list, I have data on insect survival in different cages; these have the following structure: deathtime status id cage S F G L S 1.5 1 1 C1 8 2 1 1 1 1.5 1 2 C1 8 2 1 1 1 11.5 1 3 C1 8 2 1 1 1 11.5 1 4 C1 8 2 1 1 1 There are 81 cages and

Dear R users, I have a question regarding the use of xyplot in the lattice() package. I have two factors (each with two levels), and I??d like to change the order of the panels in a 2x2 panel layout from the default alphabetic order that R uses based on the names of the factor levels. My approach is (in principle) xyplot(y~x|Factor1+Factor2) Let??s assume, my factor levels for Factor1 are A

I just downloaded TurboDelphi from edn.emarcadero.com (the full 2006 package) and am trying to install it under wine. Installation stops with a message that it needs DotNet 1.11 installed so I downloaded the .Net package from Microsoft. For some reason, this version will not install - I had previously tried .Net 2.0 and .Net 1.1. The link below leads to a file containing the command-line

<<< Thus factor analysis is in essence a model for the correlation matrix of x, ? = ?'? + ? >>> This should surely be ? = ??' + ? Also line 3 under ?Details? says <<< for a p?element row-vector x, ? >>> x is here surely a column vector, albeit the transpose of a row vector from the data matrix. cf page 322 of ?Modern Applied Statistics with S?, 4th

Hi Folks, I'm probably overlooking some small point, but can't see it. Trying the "Local trend surfaces" example from p.437 of MASS (3rd edn) by V&R, all goes well until the line contour(topo.mar$x, topo.mar$y, topo.lo$fit, levels=seq(700,1000,25), xlab="fi t", ylab="") which produces the response: Error in contour.default(topo.mar$x,

I have just put the postscript file for the first draft of a manuscript of a course on The Statistical Analysis of Stochastic Processes in Time, as well as the R code to do all of the examples, on my web page at www.luc.ac.be/~jlindsey/manuscripts.html The chapters are Part I Basic principles 1. What is a stochastic process? 2. Normal theory models and extensions. Part II Categorical state

I have just put the postscript file for the first draft of a manuscript of a course on The Statistical Analysis of Stochastic Processes in Time, as well as the R code to do all of the examples, on my web page at www.luc.ac.be/~jlindsey/manuscripts.html The chapters are Part I Basic principles 1. What is a stochastic process? 2. Normal theory models and extensions. Part II Categorical state

Is there any reason that rstandard.glm doesn't have a "pearson" option? And if not, can it be added? Background: I'm currently teaching an undergrad/grad-service course from Agresti's "Introduction to Categorical Data Analysis (2nd edn)" and deviance residuals are not used in the text. For now I'll just provide the students with a simple function to use, but I

I?m trying to find datasets that will give me residuals, after applying the lm function, with no normality, non linearity, and heteroscedacity so I can try to exemplify those cases in the linear regression model. Can you give any advice on what datasets would be appropiate? I can?t use the ones in the alr3 package because those have already been seen in class. Thank you very much :-) natorro

Dear R users, suppose I have a matrix of observations for which I calculate all pair-wise correlations: m=matrix(sample(1:100,replace=T),10,10) w=cor(m,use="pairwise.complete.obs") How do I extract only those correlations that are >0.6? w[w>0.6] #obviously doesn?t work, and I can?t find a way around it. I would very much appreciate any help! Best wishes Christoph (using R

Background: OS: Linux Mandrake 10.1 release: R 2.0.0 editor: GNU Emacs 21.3.2 front-end: ESS 5.2.3 --------------------------------- Colleagues I have a wind speed time series with a normal frequency distribution and a spike in the 5 metres/second bin. The most likely explanation is that the instrument was returning duplicate values at this speed. To check this, I want to extract all the unique

Dear R-helpers, I have a time series analysis problem in R: I want to analyse the output of my simulation model which is proportional cover of shrubs in a savanna plot for each of 500 successive years. I have run the model (which includes stochasticity, especially in the initial conditions) 17 times generating 17 time series of shrub cover. I am interested in a possible periodicity of shrub