similar to: Subsetting a matrix

Hi, I have a Dell T710 with 4 X 10G ethernet interfaces (2 X Dual port Intel 82599 cards). It is running FreeBSD RELENG_8 last updated on July 13. What I see is packet loss (0 - 40%) on IPv6 packets in vlans, when the machine is not the originator of the packets. Let me try to describe a little more. If a neigbouring machine ping6 it, there will be packet loss. If it act as a router for ipv6,

Greetings, The following question has come up in an off-list discussion. Is it possible to construct a regular expression 'rex' out of two given regular expressions 'rex1' and 'rex2', such that a character string X matches 'rex' if and only if X matches 'rex1' AND X does not match 'rex2'? The desired end result can be achieved by logically combining

Dear all, What is the quickest and most efficient way to diff two data frames, so as to obtain a vector of indices (or logical) for rows/columns that differ in the two data frames? For example, > Xe <- head(mtcars) > Xf <- head(mtcars) > Xf[2:4,3:5] <- 55 > all.equal(Xe, Xf) [1] "Component 3: Mean relative difference: 0.6863118" [2] "Component 4: Mean relative

Dear R'sians, Would really appreciate if you could suggest a more efficient way to order the columns of a dataset. The column names of the dataset contain indices separated by a period. Following are examples of my code and the dataset. oC <- function(tg=x2) { lth <- length(grep("T",names(tg))) thix <-

Hi list, since we activated 10gbe on ixgbe cards + jumbo frames(9k) on 9.0 and now on 9.1 we recognize that after a random period of time, sometimes a week, sometimes only a day, the system doesn't send any packets out. The phenomenon is that you can't login via ssh, nfs and istgt is not operative. Yet you can login on the console and execute commands. A clean shutdown isn't possible

Hello, I have used the arima.sim function to generate a lot of time series, but to day I got som results that I didn't quite understand. Generating two time series z0 and z1 as eps <- rnorm(n, sd=0.03) z0 <- arima.sim(list(ar=c(0.9)), n=n, innov=eps) and z1 <- arima.sim(list(ar=c(0.9)), n=n, sd=0.03), I would expect z0 and z1 to be qualitatively similar. However, with n=10 the

Hi, I've estimated a simple kernel density of a univariate variable with density(), but after I would like to find out the CDF at specific values. How can I do it? thanks for your help, with it I am very close to finish my first little bit more serious work in R, Viktor

I have written the following function to calculate the weighted mean difference for univariate data (see http://www.xycoon.com/gini_mean_difference.htm for a related formula). Unsurprisingly, the function is slow (compared to sd or mad) for long vectors. I wonder if there's a way to make the function faster, short of creating an external C function. Thanks very much for your advice. gmd

Dear R-list members, I have a problem with translating a mathematica script into R. The whole script is at the end of the email (with initial values for easy reproduction) and can be pasted directly into R. The problematic part (which is included below of course) is <--- Original Mathematica ---> (* p_svbar *) UiA = Ni (Dsi - 2Di A + A^2)/2; UiiA = Nii (Dsii - 2Dii A + A^2)/2; psvbar =

In the document "R Data Import/Export", section "Output to connections", there is the following portion of code: ## convert decimal point to comma in output, using a pipe (Unix) zz <- pipe(paste("sed s/\\./,/ >", "outfile"), "w") cat(format(round(rnorm(100), 4)), sep = "\n", file = zz) close(zz) ## now look at the output

Hi Folks, Thanks to several people's suggestions and clarifications, I think I have implemented a function which computes the conditional mean and covariance matrix of a subset of the dimensions of an MV-normal variable, given the values on the other dimensions (these conditioning value can be presented as a matrix, to deal with several cases at once). The code is below, for anyone who would

I have justed upgraded R v1.7.0 on Windows NT 4 and have installed the latest RMySQL (version 0.5-1)and DBI (version 0.1-5) packages. When I issue the following commands (tactfully adjusted) R just crashes and disappears, any ideas? require(RMySQL) m <- dbDriver("MySQL") con <- dbConnect(m, dbname="xxx", user="xxx", password="xxx",

> -----Original Message----- > From: r-help-bounces at stat.math.ethz.ch > [mailto:r-help-bounces at stat.math.ethz.ch]On Behalf Of Caio Lucidius > Naberezny Azevedo > Sent: 01 September 2005 12:09 > To: Help mailing list - R > Subject: [R] Multivariate Skew Normal distribution > > > Hi all, > > Could anyone tell me if there is any package (or function)

Hi all, I'd like to quantize a variable to map it into a limited set of integers for use with a colormap. "image" and filled.contour" do this mapping inside somewhere, but I'd like to choose the colors for plotting a set of polygons. Is there a pre-existing function that does something like this well? i.e., is capable of using 'breaks'?

Hello, How can I obtain the likelihood ratio of a Poisson regression model? Regards. _____________________________________________ dr. Marziliano Ciro Facolta' di Economia Universita' degli Studi di L'Aquila p.zza del Santuario, 19 67040 Roio Poggio, L'Aquila tel.: 0862 434836 fax: 0862 434803

I am learning glm function, but how do you fit data using exponential distribution with glm? In the help file, under "Family Objects for Models", no ready made option seems available for the distribution as well as for other distributions satisfying GLM requirements not listed there.

Dear list, Does anyone know how to fit the power law distribution? I have the empirical distribution and would like to check whether it fits the power law (with the power estimated from the data). Any hints are appreciated. Tanks a lot! Galina [[alternative HTML version deleted]]

Hello... Is it possible to use "density" or another kernel density estimator to identify the mode of a distribution? When I use 'density', the resulting density plot of my data is much cleaner than the original noisy histogram, and I can clearly see the signal that I am interested in. E.g., suppose my data is actually drawn from two or more normal (or other)

Hi R-users,  I have a data from multi skew t and would like to transform each of the data to uniform data.  I tried using 'pmst' but only got one output:   > rr1 <- as.vector(r1);rr1  [1]  0.7207582  5.2250906  1.7422237  0.5677233  0.7473555 -0.6020626 -2.1947872 -1.1128313 -0.6587316 -1.1409261     > pmst(rr1, xi=rep(0,10), Omega=diag(10), alpha=rep(1,10), df=5) [1] 3.676525e-09

Dear R-help list members, I have created a package 'mnormt' with facilities for the multivariate normal and t distributions. The core part is simply an interface to Fortran routines by Alan Genz for computing the integral of two densities over rectangular regions, using an adaptive integration method. Other R functions compute densities and generate random numbers. The starting