similar to: Calculating Goodman-Kurskal's gamma using delta method

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)

the method is described in the article:goodman leo A.,a modified multiple regression approch to analysis of dischotomous variables",american sociological review 33(hebruary):28-46 thank you in advance:)

Dear r-helpers! I want to classify my vegetation data with hierachical cluster analysis. My Dataset consist of Abundance-Values (Braun-Blanquet ordinal scale; ranked) for each plant species and relev?. I found a lot of r-packages dealing with cluster analysis, but none of them is able to calculate a distance measure for ranked data. Podani recommends the use of Goodman and Kruskals' Gamma for

Dear List, I would like to calculate the Goodman-Kruskal gamma for the predicted classes obtained from an ordinal regression model using lrm in the Design package. I couldn't find a way to get gamma for predicted values in Design so have found previous positings suggesting to use : Rcorr.cens(x, S outx = TRUE) in the Hmisc package My question is, will this work for predicted vs

The Goodman/Kruskal gamma is a nice descriptive rank-order correlation statistic, often used in psychology. It is nice because it is easy to understand. It takes all pairs of values of each variable and asks whether they are congruent (S+ is the number in the same order for both variables) or discordant (S-, opposite ranking). The statistic is (S+ - S-)/(S+ + S-). It is like tau except for the

Hi I need to know which package in R calculates the Goodman Kruskal's tau statistic for nominal data. Also is there any implementation for multiple classification analysis (Andrews at al 1973) in R? Any information on this would be greatly appreciated. Thank you Upasna -- --------------------------------------------------------------------- Upasna Sharma Research Scholar Shailesh J. Mehta

On Wed, 1 Aug 2007, Upasna Sharma <upasna at iitb.ac.in> wrote: > From: "Upasna Sharma" <upasna at iitb.ac.in> > Subject: [R] Goodman Kruskal's tau > > I need to know which package in R calculates the Goodman Kruskal's > tau statistic for nominal data. Also is there any implementation for > multiple classification analysis (Andrews at al 1973) in R?

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

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]]

Hi, Quick question. I'm working on training an SVM. I have a dataframe with about 50 columns. I want to train on 46 of them. Is there a way to say "All except columns 22,23,25 and 31"? It would be nice to not have to do +c1 +c2 +c3 +c4, etc for all 48 columns. Thanks! -N [[alternative HTML version deleted]]

Hello all, After beating my head against the wall for a few hours, I give up. I have two problems. 1. If I use seq() to generate a POSIXct series that crosses a daylight savings to stardard time change I get two values for the first day of change. The time change is Nov 6,2011. The value for Nov 7 turns into 23:00 on Nov 6, thus two values for Nov 6. (see below) So I put a time value (noon)