similar to: Cross-checking a custom function for separability indices

Unsubscribe -----Original Message----- From: r-help-request at r-project.org Date: Wed, 05 May 2010 12:00:09 To: <r-help at r-project.org> Subject: R-help Digest, Vol 87, Issue 5 Send R-help mailing list submissions to r-help at r-project.org To subscribe or unsubscribe via the World Wide Web, visit https://stat.ethz.ch/mailman/listinfo/r-help or, via email, send a message with subject

Hola queridos usuarios de R-HELP-ES Primero que nada, muchas gracias a todo aquellos que me prestaron ayuda en mi anterior pregunta, fue de gran utilidad. A lo siguiente, tengo ahora otras preguntas, que bajo mis conocimientos las considero complejas, espero que me puedan ayudar, se los agradezco de antemano. Necesito realizar las siguientes operaciones (#Operación general) a un conjunto de 18

I've calculated as follows: matusita<-function(f1,f2,lw,up){ fmatu<-function(x) ( sqrt(f1(x)) - sqrt(f2(x)) )^2 sqrt (integrate( fmatu, lower=lw, upper=up, subdivisions=1000000)$value) } Josué Almansa Unitat de Recerca en Serveis Sanitaris Institut Municipal d'Investigació Mèdica, IMIM c/ Doctor Aiguader, 80 08003 Barcelona e-mail: jalmansa@imim.es

Greets to the list! I am aware that this topic has been discussed several times. And I've read quite some related posts [1]. Yet, can't seem to give a solution to my problem. I have 6 data frames consisting of 6 rows x 7 columns put together from other data.frames. Something like: a b c d e f g v1 # # # # # # # v2 # # # # # # # v3 # # # # # # # v4 # # # # # # # v5 # # # # # # # v6

Hi! My question(s) in the end might be silly but I am no expert on this, so here it goes: Noy-Meir (1973), Pielou (1984) and a few others have pointed to non-centered PCA being in some cases useful. They clearly explain that "it is the case" when multi-dimensional data display distinct clusters (which have zero, or near-zero, projections in some subset of the axes) and the task is

Dear R-list, Among the (R-)tools, I've seen on the net, for (bivariate) Principal Component scatter plots (+histograms), "plotpc" [1] is the one I like most. By default it performs PCA on a bivariate dataset based on R's "princomp()" (which is the eigenvector-based algebraic solution to PCA). I would like to modify "plotpc()" in order be able, as an

Hi R-list. This is my first post. I'll try to be as precise as possible with the difficulty I have to "get things done". I have a hard time trying to construct a double "for" loop and create within the inner loop new objects (in this case vectors). I posted this question in a non-directly related with pure R-problems list (in grass-stats). In addition, I think I

On 25.10.2016 16:28, Nicolai Hähnle wrote: > But I fear that this path leads to eternal fuzziness. Let me try a > completely different approach to define what we need by augmenting the > semantics of IR with "divergence tokens". In addition to its usual > value, every IR value carries a "divergence set" of divergence tokens. > > The basic rule is: the

Hello, Yes? Where is allActive defined, I couldn't find it. Basically, a BB is control divergent if it's execution depends on a branch that itself depends on a divergent ssa value. On Fri, Jul 21, 2017 at 4:13 PM, Zaks, Ayal <ayal.zaks at intel.com> wrote: > What would be the definition of “isControlDivergent(BasicBlock*)”; the > complementary of “allActive(BasicBlock*)” –

Hello, It seems to me that our current DivergenceAnalysis does not save which BasicBlocks may suffer from divergent control. Am I correct? I want to modify our DivergenceAnalysis to add a "bool isControlDivergent(BasicBlock*) const" method and save in the divergence propagator the basicblock that are divergent. I am not sure that is entirely correct, if you have input on that please

I tried to reduce the test case in https://bugs.llvm.org/show_bug.cgi?id=42706. Here it is crashing opt: $ ~/llvm-debug/bin/opt -use-gpu-divergence-analysis -divergence stripped.ll WARNING: You're attempting to print out a bitcode file. This is inadvisable as it may cause display problems. If you REALLY want to taste LLVM bitcode first-hand, you can force output with the `-f' option.

On the surface this seems pretty simple, but I flummoxed. I have two sets of numbers they bounce around zero, positive one and negative one. They have a relationship between them, where one diverges away from the other. I want create a second set of numbers that tracks that divergence. #Lets make some data like mine, kinda Firstset <- runif(100, min = -1 , max =1) Secondset <- runif(100,

Dear experts, I have in all 14 matrices which stands for gene expression divergence and 14 matrices which stands for gene sequence divergence. I have tried joining them by using the concatanation function giving SequenceDivergence <- c(X1,X2,X3,X4,X5,X6,X7,X8,X9,X10,X11,X12,X13,X14) ExpressionDivergence <- c(Y1,Y2,Y3,Y4,Y5,Y6,Y7,Y8,Y9,Y10,Y11,Y12,Y13,Y14) where X1,X2..X14 are the

*Hi, I am considering a language extension to Clang for optimizing GPU programs. This extension will allow the compiler to use different optimization strategies for divergent and non-divergent branches (to be explained below). We have observed significant performance gain by leveraging this proposed extension, so I want to discuss it here to see how the community likes/dislikes the idea. I will

Dear all, I have a so large image (43,000 x 18,000 pixels) and I need clip this image with a smallest one (1000x1000 pixels). I can read the second image using rgdal package. But the first image can´t be read on my system because if memory limitation (I have about 2GB availabe). So I would like hear from you if anyone have some suggestin in this regards. I have also ArcGis 8.6 ans Erdas 8.3

In our experience, as Owen also suggests, a pragma or a language extension can be avoided by a combination of static and dynamic analysis. We prefer this approach in our compiler ;) Regards, Vinod On Sat, Jan 24, 2015 at 12:09 AM, Owen Anderson <resistor at mac.com> wrote: > Hi Jingyue, > > Have you considered using dynamic uniformity checks? In my experience you > can

Hi all, I have some wind data (U and V components) and I would like to compute Vorticity and Divergence of these fields. Is there any R function that can easily do that? Thanks in advance for any help Igor Oliveira CSAG, Dept. Environmental & Geographical Science, University of Cape Town, Private Bag X3, Rondebosch 7701. Tel.: +27 (0)21 650 5774 South Africa Fax: +27 (0)21

> On Dec 6, 2017, at 02:28, Haidl, Michael <michael.haidl at uni-muenster.de> wrote: > > The IR goes through a backend agnostic preparation phase that brings it into SSA from and changes the AS from 0 to 1. This sounds possibly problematic to me. The IR should be created with the correct address space to begin with. Changing this in the middle sounds suspect. > After this

Hallo! I have a vector of ID's like so, id <- c(1,2,2,3,3,3,4,5,5) I would like to create a [start,stop] pair of vectors that index the first and last observation per ID. For the ID list above, it would look like 1 1 2 3 4 6 7 7 8 9 I haven't worked with indexes/data manipulation much in R, so any pointers would be helpful. Many thanks! ~~~~~~~~~~~~~~~~~~~ -Robin Jeffries Dr.P.H.

Simply put, I want to subset the data frame 'a' where 'y=0'. > a <- as.data.frame(cbind(x=1:10, y=c(1,0,NA,1,0,NA,NA,1,1,0))) > a x y 1 1 1 2 2 0 3 3 NA 4 4 1 5 5 0 6 6 NA 7 7 NA 8 8 1 9 9 1 10 10 0 > names(a) [1] "x" "y" > table(a$y) 0 1 3 4 > table(a$y, useNA="always") 0 1 <NA> 3 4