similar to: Group averages

root@Delta:~# tc filter add dev ppp0 parent 1:1 flowid 1:5 protocol ip Unknown filter "flowid", hence option "1:5" is unparsable root@Delta:~# tc filter add dev ppp0 parent 1:1 classid 1:5 protocol ip Unknown filter "classid", hence option "1:5" is unparsable I don''t understand why it does not work. Can anybody explain me this problem? --

respectd sir,  i am working on regional frequency analysis of flood flow data and want to use packages lmomRFA, lmom, imomco,etc andby using these i want to find RMSE , errorbounds and absolute biase but could not make it clear to use, please help regards atta muhammad asif assistant professor atta_ycc@yahoo.com [[alternative HTML version deleted]]

Hello list. I just installed and configured my first Samba-3 PDC and I succeeded immediately with the "join" operation with a Win2k SP4 client. As I afterwards rebooted and tried to logon with the domain user, both root and regular user, I got an error messagge telling me that it was unable to create \\servername\root\profile.pds. In fact, my /home/profiles directory remains empty (no

Hi All, I have a HP DL 580 with 4 3 GHz CPUs and 4 GB RAM. I'm running Oracle on it. Throughout the day I am getting high load averages (6 - 18) and at the same time I see context switching go over 300,000. Sometimes over 500,000. This is slowing the system down to a crawl. My OS is RHEL 3 AS Update 4 with the 2.4.21-32.0.1.ELsmp kernel. Any ideas on why this is happening and how to fix

I have used smooth.ppp in spatstat to create a smoothed surface plot based on randomly selected depths across a lake (as marks). I wonder if based on the smoothed surface plot if I can calculate the average depth for each 10x10 grid square across the lake. I can't see any obvious way of doing this and would appreciate some pointers. Many thanks, Graham [[alternative HTML version

I am stuck at the following problem. I have two moving averages. One is faster than another. After plotting them I need to shade area between them in green when the faster is above slower and red where faster is below slower. Something like this: http://charts.stocktwits.com/production/original_9205513.png?1345576091 I tried with polygon but I can't do it. Any hints? Regards olo -- View

Problem as follows: 1) Plug in an external USB drive. 2) Mount it anywhere. Doesn't matter how. 3) Copy a few GB of data to the drive from a non-USB disk. 4) Watch the load average "climb" to 5.x, sometimes 10.x or more. Why? This on an otherwise unloaded system. Doesn't matter how many cores, how much RAM, 32/64 bit, etc. Why should copying some files to a USB drive cause

I want to get subsets averaged on numeric variables number 5:13 but I get the error below that I cannot understand. > is.factor(dat$Statut) [1] TRUE > s<-ave(dat[,5:13],dat$Statut) Error in [<-.data.frame(*tmp*, , value = if (n) { : Argument "i" is missing, with no default Thanks in advance --------------- Charles RAUX, Laboratoire d'Economie des Transports

Hi I have a table that goes data cluster_ac clockrate age class 7337 0.9 0.001 alpha_proteins 7888 0.1 0.78 beta proteins etc The class column can have 7-8 different unique values While the clockrate and age columns are floats varying from 0 to 1. I wish to get the average clockrate across each of the classes for this data. I would appreciate your help

Given a vector of numeric of length n, I need to find segments that are >= 0.2, compute the average of individual segments, and replace the original values in each segment by their corresponding averages. For example, there are three segments that are >= 0.2, the average of 1st segment is 0.3, 2nd is 0.5, and the 3rd is 0.5333333 >

Hello I have time data which is in hh:mm:ss format and I need to calculate averages for this data. I tried converting the data as integer so that I could calculate the average, but it doesn't serve the purpose. I tried using Chron package also. But I am stuck up as to how to deal with the time data. Please guide me as to how to deal with Time data in R. Thank you in advance Regards Sunita

Dear all, I have a data frame of 2160 rows and 4320 columns, which I hope to condense to a smaller dataset by finding averages of 6 by 6 blocks of values (to produce a data frame of 360 rows by 720 columns). How would I go about finding the mean of a 6 x 6 block, then find the mean of the next adjacent 6 x 6 block, and so on, until the whole data frame has been covered? One slight twist is that

Hello all, Have some time series data stored in a data.frame, and am plotting it with ggplot2 (which is totally awesome). I have explored the documentation and mailing list archives, and I can't see any way to plot a 'smoother' that is just the K-step moving average. For example, imagine I had a data.frame called 'sleep' with 'date' as the date (from as.Date()) and

Hi R users, I have a dataset with multiple variables and i'm trying to weigh average depths for fish species per year by their abundance (CPUE. I have tried the weighted.mean function but as i have two columns for the x value the lenghts differ with the w (CPUE). How do I solve this problem? So far I have tried this: data<-by(allspecies, list(allspecies$Depth, allspecies$Year),

Hello, I'm very new to R, and so my question is simple. I have data record with 80 years of daily temperatures in one long string. The dates are also recorded, in YYMMDD format. I'd like to learn an elegant simple way to pull out the annual averages. (Obviously, every 4th year has 366 days.) I know I can set up a formal loop to create annual records and then average. But R

Hi lattice users, I would like to add 5-year moving averages to my double y-plot. I have three factors needs to be plotted with moving averages in the same plot. One of these reads off y-axis 1 and two from y-axis 2. I have tried to use the rollmean function from the zoo-packages, but I fail in insering this into lattice (I am not an experienced lattice user). I want to keep the data points in

This is my situation and I am running into dead ends. We have a server with about 400GB of data that we are trying to backup with rsync. On the content1 server we had rsyncd.conf as: [content1] path = / comment = Backup list = no read only = yes hosts allow = 192.168.22.181 hosts deny = * uid = root gid = root and on the backup server we had a crontab entry as follows:

I have an array with 44800 columns and 24 rows I would like to compute the row average for the array 100 columns at a time, so I would like to end up with an array of 24 rows x 448 columns. I have tried using apply(dataset, 1, function(x) mean(x[])), but I am not sure how to get it to take the average 100 columns at a time. Any ideas would be welcomed. thanks, Spencer [[alternative HTML

Dear Colleagues, I have a dataframe with variables: [1] "ID" "category" "a11" "a12" "a13" "a21" [7] "a22" "a23" "a31" "a32" "b11" "b12" [13] "b13" "b21"

Dear all, If I have the following data frame: > set.seed(21) > df1 <- data.frame(col1=c(rep('a',5), rep('b',5), rep('c',5)), col4=rnorm(1:15)) col1 col4 1 a 0.793013171 2 a 0.522251264 3 a 1.746222241 4 a -1.271336123 5 a 2.197389533 6 b 0.433130777 7 b -1.570199630 8 b -0.934905667 9 b 0.063493345 10 b