similar to: generating many matrices

Dear helpers, I'm using R version 2.8.0. Suppose that I have a small data set like below. [,1] [,2] [,3] [,4] a 1 1 0 0 b 0 1 1 0 c 1 1 1 0 d 0 1 1 1 First, I'd like to find row sum of values uniquely present in each row, but only sequentially from the top row, meaning that if the value is shown in the above row(s) already, the

Dear R-list Suppose I have a data set stored in hmet, for which I did get confidence limit on a linear regression as shown below. My question is how I can subset only data points which are within the confidence limit. Thank you. Keun-Hyung --------------------------------------------------------------- Al=rnorm(100, 3) Cd=rnorm(100, 0.2) hmet=data.frame(Al=Al, Cd=Cd) plot(Al,

Dear all, I'm using R2.8 version, and am trying to do NMDS and calculate other diversity indices in vegan package. The problem is that it works with a small set of data (43 X 23; row by column), but the following error message comes up with a larger data set (43 X 104) (it seems not large to me at all). I made it sure that all data are of numeric type as required. >gh1.H=diversity(gh1)

Here is a clean version. I did this with nls and it works (see below), but I need to do it with optim. Keun-Hyung # optim vol<-rep(c(0.03, 0.5, 2, 4, 8, 16, 32), 3) time<-rep(c(2,4,8),each=7) p.mated<-c(0.47, 0.48, 0.43, 0.43, 0.26, 0.23, NA, 0.68, 0.62, 0.64, 0.58, 0.53, 0.47, 0.24, 0.8, 0.79, 0.71, 0.56, 0.74, 0.8, 0.47) eury<-data.frame(vol=vol, time=time, p.mated=p.mated)

Thanks Jim for pointing out how to properly ask. Here is is my question and a small subset of the data and output. I have a data set with many blanks. The blanks should be replaced with zero once imported. I tried read.table, read.csv (R 2.8 version),or scan, but none was successful. Any suggestion, please.. thanks. Keun-Hyung >garoben=read.table("c:\\Rdata\\garoben.txt",header=T,

Hi, I have this sample data below and would like to create a list of matricies. setseed(1254) id <- c(1,1,1,1 ,2,2,2) o <- as.factor(c(1:4, 1, 3, 4)) r <- rep(.5, 7) v <- rnorm(7) s <- rnorm(7) dat <-data.frame(id, o, r, v, s) dat #> dat # id o r v s # 1 1 0.5 0.7024631 2.0813672 # 1 2 0.5 -0.5541955 0.1095156 # 1 3 0.5 -1.0418167 0.4164930 # 1

I have been unsuccessful in extracting the dispersion parameter in SPLUS 6.1 using summary or summary.glm(modelobj$dispersion) from a glm object in which the family was set to quasi. This is the syntax given in the manual. I want to write a script to bootstrap the estimate of the dispersion parameter, but cannot seem to access that value. Any suggestions? Thanks, Ed ----------

Dear list Having read through all the archives of the mailing lists, I've had no luck finding the answer to my problem. I am running a for(i in 1:n) loop and am creating a matrix, p, for each of the n observations. This matrix p is a 2x1 matrix. I am then doing the following: diagp<-diag(c(p[1,1],p[2,1])) to create a matrix with the elements of P on the diagonal (i.e. a 4x4 matrix).

Hi, I have couple of questions that those who design unconventional passes would be interested in. 1. How to move a virtual register data to another new virtual register? It seems like that there is no LLVM instruction similar to mov machine instruction. Arithmetic or logical operators could be used for integer variables but what about pointer variables? 2. What is

Hi, The source attached at the bottom is a testcase which causes a back-end error in LLVM 2.4. These types of assembly routines are mainly used in OS kernels. I checked that GCC 4.3 works for this routine. The error messsage is ... Couldn't allocate output reg for constraint 'A'! I just need help or comments so that I could analyze and fix this bug. My

Hi, I've been trying to figure out a special set of covariance matrices that causes some symmetric zero elements in the inverse covariance matrix but am having trouble figuring out if that is possible. Say, for example, matrix a is a 4x4 covariance matrix with equal variance and zero covariance elements, i.e. [,1] [,2] [,3] [,4] [1,] 4 0 0 0 [2,] 0 4

Thank your for reply. The reason why these information are needed is that I am trying to extract the program signature (e.g., control flow) out side of the binary. Conventional compiler technique adds extra checking code into the target source or target IR in an invasive manner. Since code generator combines the added code with the original one, they don't need to correlate these two

Keun Soo Yim wrote: > > Hi, > > How to correlate the LLVM IR-leve instructions and memory values > with the machine instructions and memory locations? Can you tell us what goal you are trying to accomplish that requires you to do this? There might be better ways of doing what you want. The answer to your question probably depends on whether you're trying to write a

Hello there, I?m not sure if this is the right mailing list, but I?d like to see if we can add Eucalyptus to the IaaS page here: http://libvirt.org/apps.html#iaas Please let me know what is required in order to add us? Thanks very much, *_________________________* *Eric Choi - *Product Marketing *Eucalyptus Systems* www.eucalyptus.com +1 508 348-9778 Follow us on Twitter

Hi all, I was unable to find a solution to my problem in the archives, but this might be due to a lack knowledge on the correct terminology on my part. Please forgive me if this has been explained before and please forgive me my probably clumsy way of explaining things. This is what I want to do: I have a list made up of 6 lists containing 7 4x4 matrices each. My goal is to select a large

Hi, How to correlate the LLVM IR-leve instructions and memory values with the machine instructions and memory locations? For example, if CMP instruction in machine ISA is selected for the ICMP instruction in LLVA, with the Instruction datastructure for ICMP, is it possible to get the memory address of CMP instruction? Assume that the code segment base address is given. Similarly, by

Hello, I found that round() does not behave as I expected. Have you had similar experience as following? > x<-seq(0.5,10.5,by=1) > x [1] 0.5 1.5 2.5 3.5 4.5 5.5 6.5 7.5 8.5 9.5 10.5 > round(x) [1] 0 2 2 4 4 6 6 8 8 10 10 > cbind(x,round(x)) x [1,] 0.5 0 [2,] 1.5 2 [3,] 2.5 2 [4,] 3.5 4 [5,] 4.5 4 [6,] 5.5 6 [7,] 6.5 6

Does anyone succeed at compiling Linux kernel for Sparc v8 architecture? I am currently trying to expand the regime of LLVM to Sparc kernel codes. The following is the initial error messages. Any comment is welcomed. #1. Inline Assembly Code: register struct thread_info *current_thread_info_reg asm("g6"); Error Message: include/asm/thread_info.h:77: error:

Dear all, My machine is SUN Java Workstation 2100 with 2 AMD Opteron CPUs and 16GB RAM. R is compiled as 64bit by using SUN compilers. I trying to fit quantile smoothing on my data and I got an message as below. > fit1<-rqss(z1~qss(cbind(x,y),lambda=la1),tau=t1) Error in as.matrix.csr(diag(n)) : cannot allocate memory block of size 2496135168 The lengths of vector x and y are

Hello, I am trying to obtain the partial r-square values (r^2 or R2) for individual predictors of an outcome variable in multiple linear regression. I am using the 'lm' function to calculate the beta coefficients, however, I would like to know the individual % contributions of several indepenent variables. I tried searching for this function in many R packages, but it has proven elusive