search for: wume

Dear list, When compiling the R-2.3.0 on FC4 x86_64, I got the following errors: make[3]: Entering directory `/project/scratch3/ligroup/wuming/src/R-2.3.0/src/main' gcc -Wl,--export-dynamic -L/usr/local/lib64 -o R.bin Rmain.o CConverters.o CommandLineArgs.o Rdynload.o Renviron.o RNG.o apply.o arithmetic.o apse.o array.o attrib.o base.o bind.o builtin.o character.o coerce.o colors.o complex.o

Dear list, Given a vector of logical values, say >a <- c(TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE) Are there any R functions that can tell whether there are two or more "TRUE" in a row in this vector? Thanks, Wuming

Dear list, This question is about Hidden Markov Model. Given a transition matrix, an emission matrix and a sequence of observed symbols (actually, nucleotide sequences, A, T, C and G), I hope to predict the sequence of state by Viterbi algorithm. I searched R repository for related packages. msm package has function viterbi.msm (as well as very good document), but it only works for

Hi: I use lm (linear model) to analyze 47 variables , 8 responses So I use loop to finish it . I want the program to show the results that P-value is less than 0.05. How can I cite the P-valus from lm result ? Ping The code: #using LM to model general fati for (j in 48:52) { for (i in 3:46){ gen.fat<-y_x[,j] gen.fat<-as.numeric(gen.fat) snp_marker<-y_x[,i] x<-colnames(y_x)

Dear list, In some places (for example, http://en.wikipedia.org/wiki/Support_vector_machine) , the polynomail kernel in SVM is written as (u'*v + 1)^d, while in the document of svm() in e1071 package, the polynomial kernel is written as (gamma*u'*v + coef0)^d. I am a little confused here: When doing parameter optimization (grid search or so) for polynomial kernel, does it need to tune

Dear list, I installed odesolve package (0.5-15) in R 2.3.1 in a Solaris server (Generic_118558-11 sun4u sparc SUNW,Sun-Blade-1000). The installing progress completed without errors, though several warnings like "Warning: Option -fPIC passed to ld, if ld is invoked, ignored otherwise" were outputed. However, when loading the odesolve package by library(odesolve), following error

Dear list, I have a problem on calculating the standard error of Goodman-Kurskal's gamma using delta method. I exactly follow the method and forumla described in Problem 3.27 of Alan Agresti's Categorical Data Analysis (2nd edition). The data I used is also from the job satisfaction vs. income example from that book. job <- matrix(c(1, 3, 10, 6, 2, 3, 10, 7, 1, 6, 14, 12, 0, 1, 9,

Hi list, I have a group of data. It looks like they follow a exponential distribution. In R, how can I esimate lamda, that is the rate in pexp, of the distribution and can I use Kolmogorov-Smirnov for hypothesis testing in such a situation? I have read the "8.2 Examing the distribution of a set of data" of "An Introduction to R" but I did not find any clues on this issue.

Hi I am using R for logistic regression and finding it very useful. However, I wondered if anyone could point me to any course or notes on this subject using R. All help most welcome. Stephen -- Internal Virus Database is out-of-date. Checked by AVG Anti-Virus. [[alternative HTML version deleted]]

Hello sir: Here's a question on covariance analysis which needs your help. There're 3 experiments,and x refers to control while y refers to experimental result. The purpose is to compare the "y" values across the 3 experiments. experiment_1: x:0.1 0.2 0.3 0.4 0.5 y:0.5 0.6 0.6 0.7 0.9 experiment_2: x:1 2 3 4 5 y:3 4 6.5 7.5 11 experiment_3: x:10 20 30 40 50 y:18 35 75 90

Hi, I have a 60k*600k matrix, which exceed the vector length limit of 2^32-1. But it's rather sparse, only 0.02% has value. So I save is as MarketMatrix (mm) file, it's about 300M in size. I use readMM in Matrix package to read it in. If do so, the data type becomes dgTMatrix in 'Matrix' package instead of the common matrix type. The problem is, if I run k-means only on part of

Dear all R-users, I am a new user of R and I am trying to build a discrete choice model (with more than two alternatives A, B, C and D) using logistic regression. I have data that describes the observed choice probabilities and some background information. An example below describes the data: Sex Age pr(A) pr(B) pr(C) pr(D) ... 1 11 0.5 0.5 0 0 1 40 1 0 0 0 0 34 0 0 0 1 0 64 0.1 0.5 0.2 0.2 ...

for example: > a$tic[1:10] [1] "AIR " "ABCB " "ABXA " "ACMR " "ADCT " "ADEX " [7] "ABM " "AFCE " "AG " "ATG " Can anyone please tell me how to strip the white spaces from a$tic? Thanks, Roger [[alternative HTML version deleted]]