similar to: Calculate NAs from known data: how to?

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,

hi, I have a hard time figuring this out, the kernel says: ... ix0: <Intel(R) PRO/10GbE PCI-Express Network Driver, Version - 2.5.15> port 0xecc0-0xecdf mem 0xd9e80000-0xd9efffff,0xd9ff8000-0xd9ffbfff irq 40 at device 0.0 on pci4 ix0: Using MSIX interrupts with 9 vectors ix0: Ethernet address: 90:e2:ba:29:c0:54 ix0: PCI Express Bus: Speed 5.0GT/s Width x8 ix1: <Intel(R) PRO/10GbE

I finally got a 10G card that is recognized by FreeBSD (9.1-stable): ... ix0: <Intel(R) PRO/10GbE PCI-Express Network Driver, Version - 2.4.8> port 0xecc0-0xecdf mem 0xd9e80000-0xd9efffff,0xd9ff8000-0xd9ffbfff irq 40 at device 0.0 on pci4 ix0: Using MSIX interrupts with 9 vectors ix0: RX Descriptors exceed system mbuf max, using default instead! ix0: Ethernet address: 90:e2:ba:29:c0:54

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

Hi, I'm trying to read a subset of a netcdf file into R, but although I'm relatively experienced using R, I'm still new to netCDF files, so this may be a very simple/stupid question! I've included an example of the type of file I'm looking at here. www.met.reading.ac.uk/~swp06hg/ccd1983_01-dk1_20.nc (~7Mb) It's a 2D array of the variable CCD along with its lat and

Hi David, I was about to post a reply when Bert responded. His answer is good and his comment to use the name 'dat' rather than 'data' is instructive. I am providing my suggestion as well because I think it may address what was causing you some confusion (mainly to use "which", but also the missing !) idx2 <- sample( which( (!data$var1%%2) & data$sampleNo==0 ),

For personal aesthetic reasons, I changed the name "data" to "dat". Your code, with a slight modification: set.seed (1357) ## for reproducibility dat <- data.frame(var1=seq(1:40), var2=seq(40,1)) dat$sampleNo <- 0 idx <- sample(seq(1,nrow(dat)), size=10, replace=F) dat[idx,"sampleNo"] <-1 ## yielding > dat var1 var2 sampleNo 1 1 40

Hello everybody! I have the following problem: I'd like to select a sample from a subsample in a dataset. Actually, I don't want to select it, but to create a new variable sampleNo that indicates to which sample (one or two) a case belongs to. Lets suppose I have a dataset containing 40 cases: data <- data.frame(var1=seq(1:40), var2=seq(40,1)) The first sample (n=10) I drew like

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

I'd welcome some comments or advice regarding the situation described below. The following illustrates what seems to me to be an inconsistency in the behaviour of matrix subsetting: > Z<-matrix(c(1.1,2.1,3.1,1.2,2.2,3.2,1.3,2.3,3.3),nrow=3) > Z [,1] [,2] [,3] [1,] 1.1 1.2 1.3 [2,] 2.1 2.2 2.3 [3,] 3.1 3.2 3.3 > dim(Z) [1] 3 3 >

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 A quick question. Standard errors reported by gee/yags differs from the ones in geeglm (geepack). require(gee) require(geepack) require(yags) mm <- gee(breaks ~ tension, id=wool, data=warpbreaks, corstr="exchangeable") mm2 <- geeglm(breaks ~ tension, id=wool, data=warpbreaks, corstr="exchangeable", std.err = "san.se") mm3 <- yags(breaks ~

I tried multiple imputation with aregImpute() and fit.mult.impute() in Hmisc 3.8-3 (June 2010) and R-2.12.1. The warning message below suggests that summary(f) of fit.mult.impute() would only use the last imputed data set. Thus, the whole imputation process is ignored. "Not using a Design fitting function; summary(fit) will use standard errors, t, P from last imputation only. Use

Hi everybody, I am quite new to data imputation, but I would like to use the R package ' Amelia II: A Program for Missing Data '. However, its unclear to me how the input for amelia should look like: I have a data frame consisting of numerous coulmns, which represent different experimental conditions, whereby each column has 3 replicates. I want amelia to perform an imputation across

Hello, I am attempting to train a random forest model using the randomForest package on 500,000 rows and 8 columns (7 predictors, 1 response). The data set is the first block of data from the UCI Machine Learning Repo dataset "Record Linkage Comparison Patterns" with the slight modification that I dropped two columns with lots of NA's and I used knn imputation to fill in other gaps.

Hello! If I understand this listserve correctly, I can email this address to get help when I am struggling with code. If this is inaccurate, please let me know, and I will unsubscribe. I have been struggling with the same error message for a while, and I can't seem to get past it. Here is the issue: I am using a data set that uses -1:-9 to indicate various kinds of missing data. I changed

Hi! Does anyone know how to do the test for goodness of fit of a logistic model (in rms package) after running fit.mult.impute? I am using the rms and Hmisc packages to do a multiple imputation followed by a logistic regression model using lrm. Everything works fine until I try to run the test for goodness of fit: residuals(type=c("gof")) One needs to specify y=T and x=T in the fit. But

Hi, I am a long time SPSS user but new to R, so please bear with me if my questions seem to be too basic for you guys. I am trying to figure out how to analyze survey data using logistic regression with multiple imputation. I have a survey data of about 200,000 cases and I am trying to predict the odds ratio of a dependent variable using 6 categorical independent variables (dummy-coded).

Dear all, I am using transcan to impute missing values (single imputation). I have several dichotomous variables in my dataset, but when I try to impute the missings sometimes values are imputed that were originally not in the dataset. So, a variable with 2 values (severe weight loss or no/limited weight loss) for example coded 0 and 1, shows 3 different values after imputation (0, 1 and 2). I