similar to: calling R-functions from C++ code

One more question... I need to use the Loess() function in the package modreg. What is the argument "formula" meant to be? A -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not the

I have a probably basic problem concerning the R language. I will write some small R programs but don't really know how to start. Do I have to create my files in some editor like emacs or can I write my code in the R prompt? How to compile the code? I haven't found any good manual parts about this subject. regards A.P

Just a reminder, the Cambridge social is today. The weather is lovely, so we'll be outside by the river. Cheers, Renato On Jun 14, 2013 11:09 AM, "Renato Golin" <renato.golin at linaro.org> wrote: > Hi folks, > > Next Wednesday, 19th June, we'll be on Fort St. George, at 7:30pm > > http://gkpubs.co.uk/pubs-in-cambridge/fort-st-george-pub/ > > Weather

Hi! In a current project, I am fitting loess models to subsets of data in order to use the loess predicitons for normalization (similar to what is done in many microarray analyses). While working on this I ran into a problem when I tried to predict from the loess models and the data contained NAs or NaNs. I tracked down the problem to the fact that predict.loess will not return a value at all

Dear All, I am facing a problem in calling an user defined R function from Java through JRI. The user defined R function does a loess normalization on micro array data ( find in the limma package of BioConductor) and the last 2 lines of the R Code is : MA <- normalizeWithinArrays(RG, method="loess") return(MA$A) # where MA$A is the column A of MA. Now while calling it in Java, I

The Boathouse is nice - on the river and with reasonable beer and food. The Old Spring is also quite nice, has big tables outside, and is usually quite quiet midweek. David (Who has not yet completed the process of performing an exhaustive survey of Cambridge pubs) On 19 Jun 2013, at 16:46, Steve Montgomery <stephen.montgomery3 at btinternet.com> wrote: > Just cycled past The Fort.

Just cycled past The Fort. It's very busy because there's a fair on the common. Any plan B in case it's still full later? On 19 Jun 2013, at 15:20, Renato Golin <renato.golin at linaro.org> wrote: > Just a reminder, the Cambridge social is today. The weather is lovely, so we'll be outside by the river. > > Cheers, > Renato > > On Jun 14, 2013 11:09 AM,

Hi folks, Next Wednesday, 19th June, we'll be on Fort St. George, at 7:30pm http://gkpubs.co.uk/pubs-in-cambridge/fort-st-george-pub/ Weather permitting, there's a very nice beer garden and a good selection of beers. During this lame summer, we'll probably be repeating the same pub in hope the shy sun will come out, so the next one, on the 17th of July (it's in the calendar),

Hi, I have a set of measurements that are made on a daily basis over many years. I would like to produce a *non-parametric* smooth of these data to estimate the seasonal cycle - to achieve this, I have been using the cyclic cubic splines from the mgcv package. This works superbly in most situations, but not all. The problem is that for various practical reasons the data is not available all year

Only because in my next passes I change the CFG significantly and it is very hard to maintain the values of the Phi nodes. Alexandra ________________________________ From: Tobias Grosser <tobias at grosser.es> To: Jimborean Alexandra <xinfinity_a at yahoo.com> Cc: "llvmdev at cs.uiuc.edu" <llvmdev at cs.uiuc.edu>; "luismastrangelo at gmail.com"

Hello Tobi, You are right, we need to run some other passes before running the scalar evolution pass. The sequence that I run for this example is -O3 -loop-simplify -reg2mem.  This is why I did not obtain the expressions depending on the loop indices. So I removed the reg2mem pass and scalar evolution computes the correct functions. However, I need to run the reg2mem pass (or any other that

Dear all, I have been using normalize.loess and I get the following error message when my matrix contains NA values: > my.mat = matrix(nrow=100, ncol=4, runif(400) ) > my.mat[1,1]=NA > my.mat.n = normalize.loess(my.mat, verbose=TRUE) Done with 1 vs 2 in iteration 1 Done with 1 vs 3 in iteration 1 Done with 1 vs 4 in iteration 1 Done with 2 vs 3 in iteration 1 Done with 2 vs 4 in

Ok, thank you, I will have a look and reply with questions if necessary. Does it take into consideration the existing phi nodes? Alexandra ________________________________ From: Tobias Grosser <tobias at grosser.es> To: Jimborean Alexandra <xinfinity_a at yahoo.com> Cc: "llvmdev at cs.uiuc.edu" <llvmdev at cs.uiuc.edu>; "luismastrangelo at gmail.com"

>>>>> "Jose" == Jose Ramon G Albert <toots at info.com.ph> writes: Jose> I have just downloaded this freeware version of R (which seems Jose> to be a clone of S). I was wondering if anyone knows where I Jose> could obtain R or S functions which provide nonparametric Jose> regression curves, e.g. kernel estimators or smoothing Jose> splines.

Hi All, I am trying to understand panel functions. Let's use this example. library(lattice) time<-c(rep(1:10,5)) y <-time+rnorm(50,5,2) group<-c(rep('A',30),rep('B',20)) subject<-c(rep('a',10),rep('b',10),rep('c',10),rep('d',10),rep('e',10)) myData <-data.frame(subject,group,time,y) head(myData) Plot 1 xyplot(y ~ time

Hello, I was hoping that someone familiar with the implementation details of the loess algorithm might be able to help me resolve some difficulties I am having. I am attempting to reproduce some of the functionality of the loess() function in C++. My primary motivation is that I would like to understand the algorithm in detail. So far I have managed to create a working port in C++ for the

On 07/27/2011 03:11 PM, Jimborean Alexandra wrote: > Hello, > > How can I compute the functions on the loop iterators used as array > indices? > > For example: > > for i = 0, N > for j = 0, M > A[2*i + j - 10] = ... > > Can I obtain that this instruction A[2*i + j - 10]= .. always accesses > memory using a function f(i,j) = 2*i + j - 10 + base_address_of_A

Thanks for the suggestions, one option i was thinking was to center the universal channel and sample channels by normalising the medians of each column of the matrix on each channel. But I don't know if it is appropriate to do a loess after this? Does the quantile option actually do this? Peter At 06:59 PM 7/28/2004, you wrote: >At 06:02 AM 29/07/2004, Peter Wilkinson wrote:

Suppose that I'm working on Hadley's diamond dataset and I want to review the relationship between price, colour and carat. I might run the following: library(ggplot2) #plot scatter and add some hex binning q<-qplot(carat,price,data=diamonds, geom=c("hex"), main="Variability of Diamond Prices by Carat and Colour") #facet to get one scatter for

Hi, I'm having a problem getting the panel.average function to work as I expect it to in a lattice plot. I wish to draw lines between the averages of groups of y-values at specific x-values. I have created a dataset below which is similar to my real data. I also show an example of using panel.loess in place of panel.average; it performs in a manner similar to what I want panel.average to do