similar to: Has anyone used SIAR package add on?

Dear List, I would greatly appreciate help on the following matter: The RuleFit program of Professor Friedman uses partial dependence plots to explore the effect of an explanatory variable on the response variable, after accounting for the average effects of the other variables. The plot method [plot(summary(rq(y ~ x1 + x2, t=seq(.1,.9,.05))))] of Professor Koenker's quantreg program

Dear List, I would appreciate help on the following matter: I am aware that higher dimensional contingency tables can be analysed using either log-linear models or as a poisson regression using a generalized linear model: log-linear: loglm(~Age+Site, data=xtabs(~Age+Site, data=SSites.Rev, drop.unused.levels=T)) GLM: glm.table <- as.data.frame(xtabs(~Age+Site, data=SSites.Rev,

Dear R-help, Has anyone implemented sparklines in the strips of a lattice plot? What I have in mind is, say, highlighting that part of a time series that one is examining in more detail in a set of lattice plots. Regads,. Mark Difford. PS: (Andreas Loffler has implemented a simple but functional version for TeX/LaTeX: http://www.tug.org/tex-archive/help/Catalogue/entries/sparklines.html)

Help! model1 <- siarmcmcdirichletv4(data, source, tef, concdep=0, 500000, 50000) Error in matrix(1, ncol = (numsources + numiso) * numgroups, nrow = (siardata$iterations - : invalid 'ncol' value (too large or NA) In addition: Warning message: In Ops.ordered((numsources + numiso), numgroups) : '*' is not meaningful for ordered factors Previous message, but more

Dear R-core/development-team, The problem noted in the subject-line has been a problem in the last three development versions of R for Windows that I have downloaded and tested, the most recent of them being a version I downloaded this morning. Update.packages() using the graphical option, i.e. called as update.packages(ask='graphics', checkBuilt=TRUE) does not work as it should, but

Dear R-help, I posted this on 4 Oct but got no response (I wasn't even told to go away and do some more background reading ;) ). I am reposting it in the, perhaps, vain hope that someone with knowledge of the subject will reply, if only to point me in a different direction to which I am now facing. Earlier Posting:--- I am sorry if this is more of a stats question than an R-question, but I

Dear R-help, I am sorry if this is more of a stats question than an R-question, but I have found it difficult to get a clear answer by other means. Q. Would it be "wrong" to specify a nested model and retain a common intercept, e.g. lm(NH4 ~ Site/TideCode + 1) I am aware (?) that my Site-coefficients are now calculated relative to my reference Site (treatment.contrasts), *but* that

On May 24, 2011; 11:06pm Belle wrote: > Does anyone know how to run Multinomial logistical Model in R in order to > get predicted probability? Yes. I could stop there but you shouldn't. The author of the package provides plenty of examples (and two good vignettes) showing you how to do this. Suggest you do some work in that area. Look especially at how model formulas are

Dear R-users, I am a newbie to this site and a relative new-comer to S/R, so please tread lightly, for you tread... There have been several posting relating to problems with augPred() from the nlme library. Here is a "fix" for one of these problems which may lie at the root of others. In my case the problem with augPred() lay in gsummary(), which augPred() uses, causing it to fail.

I'm absolutely not brilliant with R yet and working with package SIAR. 1) SIAR reads the first column of a table.txt as "int" instead of "num". Who can help? 2) I therefore made tables with a data.frame() > that seems to work. But at the end of the loading proces of the SIARmodel, I get a warning screen with "Session Aborted". Everything crashes and I can start

Hello, I recently bought a new Macbook Pro and installed R via a disk image from an older computer - it seems to work fine. I then installed the package "siar", tried to load it via the library command and received the following messages (note the "mvtnorm" package did not appear to load correctly): trying URL

Hi there, I am trying to run an MCMC on stable isotope data from certain organisms to determine their dietary habits in the package SIAR. I have prepared my data according to Inger, R., Jackson, A., Parnell, A., Bearhop, S. : SIAR V4 (Stable Isotope Analysis in R) an Ecologist's Guide (also better known as 'SIAR for dummies'), which is as follows: - consumer data table (columns

Hi, I have a problem while loading the "siar" program in R. When I am loading siar, system does not load convexhull. On the screen I have seen such writings. The following object(s) are masked from ‘package:spatstat’: convexhull How can I load the convexhull, how can I unmask from this package? I will be appreciated if you give advice about this. Best Sukran

Hi, my name is Julio, I'm trying to run a script, specifically with the siar package on R (I have attached the script) but the program collapses on during the run. The error message says: *** caught segfault *** address 0xb31941cc, cause 'memory not mapped' Traceback: 1: .C("siarmcmcv4", as.integer(numdata), as.integer(numsources), as.integer(numiso),

Hello, I am trying to run the demoscript for the package "siar". However, using the example script and example data supplied I cannot get 1) the model to run unless I specify iterations =500 and burnin = 500 and 2) if the model does work without crashing R then the function "siarhistograms" does not work . Can anyone point out where I am going wrong? >model1 <-

Help! model1 <- siarmcmcdirichletv4(data, source, tef, concdep=0, 500000, 50000) Error in matrix(1, ncol = (numsources + numiso) * numgroups, nrow = (siardata$iterations - : invalid 'ncol' value (too large or NA) In addition: Warning message: In Ops.ordered((numsources + numiso), numgroups) : '*' is not meaningful for ordered factors Previous message, but more problems:

Hi All, I have been trying to get to plot my PCA legend outside of the PCA plot, but success still alludes me. Can you guys please advise how I can achieve this. I used locater() to obtain coordinates for below the Comp.1 axis. Using these coordinates the legend disappears. Below is the code for the PCA and legend. Thanks in advance for the help. Regards Tinus r.cols <-

Hi: I have a large dataset mydata, of 1000 rows and 1000 columns. The rows have gene names and columns have condition names (cond1, cond2, cond3, etc). mydata<- read.table(file="c:/file1.mtx", header=TRUE, sep="") I applied PCA as follows: data_after_pca<- prcomp(mydata, retx=TRUE, center=TRUE, scale.=TRUE); Now i get 1000 PCs and i choose first three PCs and make a

Hi All, I'm using the following code to produce some stacked bar graphs. *setwd("C:\\Users\\Tinus\\Documents\\NMMU\\R\\Seamounts")* *SChla <- read.csv("SM_Chla_data.csv")* * * *#Extract mean values from data file* * * *Coral <- SChla[185:223,] #Reduce SChla to Coral only* *coral <- with(Coral , aggregate(cbind(Pico, Nano, Micro), list(Depth),FUN=mean))*

Hi all, I'm trying to do model reduction for logistic regression. I have 13 predictor (4 continuous variables and 9 binary variables). Using subject matter knowledge, I selected 4 important variables. Regarding the rest 9 variables, I tried to perform data reduction by principal component analysis (PCA). However, 8 of 9 variables were binary and only one continuous. I transformed the data by