similar to: problems with rpubchem package on fedora

Hi, I am trying to use a CGI service (Pubchem PUG) via RCurl and am running into a problem where the data must be supplied via POST - but I don't know the keyword for the argument. The data to be sent is an XML fragment. I can do this via the command line using curl: I save the XML string to a file called query.xml and then do curl -d @query.xml

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':

Hi, Thanks in advance for any advice you can give me, I am very stumped on this problem... I use R every day and consider myself a confident user, but this seems to be an elementary problem.. Outline of problem: I am analysing the results of a study on protein expression in cancer tissues. I have raw intensities from 2 different types of cancer and normal tissue, which can be taken from several

Hi dear R-listers, I'm trying to fit a 3-level model using lme in R. My sample size is about 2965 and 3 factors: year (5 levels), ssize (4 levels), condition (2 levels). When I issue the following command: > lme(var~year*ssize*condition,random=~ssize+condition|subject,data=smp,method ="ML") I got the following error: Error in logLik.lmeStructInt(lmeSt, lmePars) :

Hello everyone: I'm a new member of this group. I have a question about "oneway.test". When I use "anova(lm(....))" to analysis the ANOVA, I can get the information about Sum Sq and Mean Sq. (The R code and the results are as follows.)

Hi, this question is probably very obvious but I just cant see where I might be going wrong. I'm using the lm() function to generate a linear model and then make predictions using a different set of data. To generate the model I do (tdata & pdata are matrices of observations and parameters, tdepv, pdepv are response vectors) x <- as.data.frame(tdata) x$tdepv <- tdepv

Dear R-helpers, I am developing a Mixed-Effects model for a study of immunoassays using 'lme4' library. The study design is as follows: 10 samples were run using 7 different immunoassays, 3 times each, in duplicates. Data attached. I have developed the following model: c.lme <- lmer(Result~SPL + (SPL|Assay/Run) -1, data=data) This model has excellent predictions - the Rsquared of

describe Asset, " when destroyed" do fixtures :assets, :videos, :sites, :publish_settings before(:each) do @asset = assets(:test_asset) @mock_hook = mock("hook") @asset.video.stub!(:hook).and_return @mock_hook # error occurs here end it "should call the delete hook" do @mock_hook.should_receive(:update).with("test_video",

Hi I am attempting Anova analysis to compare results from four groups (Samp1-4) which are lists of intensities from the experiment. I am doing this by first creating a structured list of the data and then conducting the ANOVA (Script provided below). Im an R beginner so am not sure if I am using this correctly. Two major questions I have are: 1) Is using the code (zzz.aov <- aov(Intensity ~

Hi, this should be an easy one, but I can't figure it out. I have a vector of tests, with their units between brackets (if they have units). eg tests <- c("pH", "Assay (%)", "Impurity A(%)", "content (mg/ml)") Now I would like to hava a function where I use a test as input, and which returns the units like: f <- function (x) sub("\\)",

Hi, I'me trying to write a function that will shuffle a vector. At the moment I'm baically making a vector of randomized indices and then making a new vector from the original one using these random indices. However, is there an alternative (more elegant) method to do this? I tried help.search('shuffle') but it does'nt return anything relevant. Thanks,

Hi all, I started to see fun of gmaps4rails gem from https://github.com/apneadiving/Google-Maps-for-Rails. After everything done. When visited the locahost, i got the following error. undefined local variable or method `acts_as_gmappable'' for #<Class: 0x31a9da8> the error is due to i have line "acts_as_gmappable" in my model. Anybody knows how this is

Using a "by() statement, I am preparing ANOVA's for multiple experiments, and using simint() to generate confidence intervals. This works fine. simint.by.fit <- by(analytes.dfr, list(Assay = analytes.dfr$analyte ), function(data) (simint(value ~ tx, data = data,type='Tukey' ) ) ) I can separately prepare plots of the confidence intervals, and I can prepare separate plots

Hi, is the following possible - in a given session I make a lot of objects and save when exiting. Usually I note down seperately what each object is about. Is it possible to attach data to any object which would essentially be a short note explaining the meaning of it? Thanks, ------------------------------------------------------------------- Rajarshi Guha <rxg218 at psu.edu>

Hi, is there a way to plot distribution curves (say normal or chi sq etc) from within R? For example I looked up the *chisq family of functions but I'm not sure as to how I would use them to generate a plot of the chi sq distribution (for arbitrary d.o.f). Thanks, ------------------------------------------------------------------- Rajarshi Guha <rajarshi at presidency.com>

Try this data(Assay) as1 <- lme(logDens~sample*dilut, data=Assay, random=pdBlocked(list( pdIdent(~1), pdIdent(~sample-1), pdIdent(~dilut-1)))) update(as1,random=pdCompSymm(~sample-1)) update(as1,random=pdCompSymm(~sample-1)) update(as1,random=pdCompSymm(~sample-1)) update(as1,random=pdCompSymm(~sample-1)) I'm

Hi, I have 3 lists, x, y, z and I'd like to perform a calculation over all the lists simultaneously. If it were a single list I could use lapply, but for more than one list I'm using a for loop. Is there an idiom that would let me use something like lapply, but the function specified to lappy would have access to an element from each list? (In Python, I would have used for a,b,c in

Hi, I need to construct a formula programaticly, and pass it to a function such as the linear mixed model lme. The help says it requires "a two-sided linear formula object describing the fixed-effects part of the model" but I do not know how to create this formula. I have tried various things using formula(x, ...), as.formula(object, env = parent.frame()) and as.Formula(x, ...)

Hi, I have a data.frame that has a categorical variable, for which I would like to look at the distribution of levels of this variable, based on a grouping of two other variables. As an example: x <- data.frame(obs=sample(c('low', 'high'),100, replace=TRUE), grp1=sample(1:10, 100, replace=TRUE), grp2=runif(100)) cut.grp1 <- cut(x$grp1, 3) cut.grp2 <- cut(x$grp2, 3)

Hi, I have a data.frame with columns named X, D1, D2, D3 I know I can get a single plot with 3 curves by doing xyplot(D1 + D2 + D3 ~ X, data) but in some cases I might have columns D1 ... D10. Is there a way to plot all 10 columns without having to specify each individual term? (By analogy with formulae in lm, I thought, xyplot(. ~ X, data) would work, but it didn't) Thanks, --