similar to: poisson fit for histogram

Sorry to bother you kind folks again with my questions. I am trying to learn as much as I can about all this, and I will admit that I don't have the proper background, but I hope that someone can at least point me in the correct direction. I have created a test matrix for what I want to do: s1 s2 s3 s4 s5 s1 10 5 0 8 7 s2 5 10 0 0 5 s3 0 0 10 0 0 s4 8 0 0 10 0 s5 7

R-help folks: Thanks in the past for your help. I have another question that I hope has a simple answer. I have searched the R home pages and the R-help archives with no hits. How can I cluster data in R using UPGMA? I am not subscribed to the list (can't keep up with all the traffic!), so I would appreciate it if you could email directly to me (or to the list and to me). Thanks, Tom

I have a matrix of similarity scores that I want to convert into a matrix of dissimilarity scores so that I can apply some clustering methods to the data. That is, high values in my matrix signify similarity and low values (zero being the lowest) signify no similarity. What functions/options in R or its packages are available for making this kind of transformation of a matrix?

this is probably not really a R specific question, if so apologies for off-topic posting: I'm interested in the probability density function of the maximum values from repeated samples of size N from a normal distribution: smp <- rnorm(N, meanval, stdev) with some mean 'meanval' and standard deviation 'stdev'. I would like to know what is the frequency distribution of

I'm trying to create a function which will allow me to subset a data set based on values of various specified variables. I also want to then apply some other function(s) (e.g., summary). This is what I've tried so far.... > test.fx <- function(dta, expvar, expval) { + newdta <- subset(dta, eval(expvar)>expval) + summary(newdta$eval(expvar)) + } > >

hi R-help! I would like to know a simple and easy way (if posible) to do the following data manipulation. I have a matrix of experimental data (with replicae in time) >experiment<-data.frame(times=c(0,0,10,10,20,20,30,30),expval=c(1,1,2,2,3,3,4,4)) > experiment times expval 1 0 1 2 0 1 3 10 2 4 10 2 5 20 3 6 20 3 7 30 4 8

Hello, I am have some interesting problems with the pam_winbind portion of samba 3.1. wbinfo -u and getent passwd works but when I login I get the following messages in /var/log/messages. Jan 5 11:09:36 hermes pam_winbind[9014]: write to socket failed! Jan 5 11:09:36 hermes pam_winbind[9014]: internal module error (retval = 3, user = `CSQ+shane' Jan 5 11:09:36 hermes PAM_pwdb[9014]: check

Hello, I am facing a problem with optimization in R from 2-3 weeks. I have some Gaussian mixtures parameters and I want to find the maximum in that *Parameters are in the form * mean1 mean2 mean3 sigma1 sigma2 sigma3 c1 c2 c3 506.8644 672.8448 829.902 61.02859 9.149168 74.84682 0.1241933 0.6329082 0.2428986 I have used optima and optimx to find the

Dear all, I want to use the deltavar() function from emdbook. I can use it directly from the command terminal but within a function it behaves weird. Working example: ---------------------- library("emdbook") fn <- function() { browser() y <- 2 print(deltavar(y*b2, meanval=c(b2=3), Sigma=1) ) } x <- 2 print(deltavar(x*b1, meanval=c(b1=3), Sigma=1) ) y<-3 fn()

Hello, I have got a question. I've got a matrix (mail end) with the colnames x, y, z. In this matrix are different measurements. x and y are risign coordinates. My question. Always, if the "x" AND "y" coordinates are the same, I want to get the mean of their z values. e.q. " x" AND "y" in line1 and line8 are identical: 29 4.5 --> mean of

Hi, Since I had upgraded from Samba 3.0.0 to 3.0.4 I have problems with ArcServe to connect to the share. Arcserve is running on a NT 4.0 box, everytime I try to connect to the samba share it says me "authenticacion failed". When I browse the share from windows explorer I have not problems. Thank you in advance Guillermo

Hello, I would like to know if there is a function in R that will test for normality and handle censored data sets. Currently, I evaluate each censored data set by the extent to which a normal scores plot approximate a straight line. For complete data sets I use shapiro.test(). Below is an example of a censored data set. data1<-c(0.00, 0.00, 0.00, 5.86, 5.17, 8.17, 5.12, 4.92, 7.08,

I propose to present on one or more of the following topics: * NFS-Ganesha Architecture, Roadmap, and Status * Architecture of the High Availability Solution for Ganesha and Samba - detailed walk through and demo of current implementation - difference between the current and storhaug implementations * High Level Overview of autoconf/automake/libtool configuration (I gave a presentation in BLR

Dear All, GSoC 2013 is coming! This means it's a good time to refresh the Open Projects pages. So, please, add your ideas there, remove old / unimportant stuff, tweak current ideas. It's really important to have these pages up-to-date by the time of GSoC (next couple of weeks). Your help is needed! -- With best regards, Anton Korobeynikov Faculty of Mathematics and Mechanics, Saint

I am developing a package for analysis of seismic data that relies on a Fortran library. Package compilation works fine on Ubuntu and Red Hat Enterprise but fails for R 2.15.3 on Mac OSX 10.8.4. I've included the entire dump below but the relevant error message seems to be: ld: warning: ignoring file libmseed/libmseed.a, file was built for archive > which is not the architecture being

I have a time series with interval of 2.5 minutes, or 24 observations per hour. I am trying to find a 1 hr moving average, looking backward, so that moving average at n = mean(n-23 : n) The time series has about 1.5 million rows, with occasional gaps due to poor data quality. I only want to take a 1 hour moving average for those periods that are complete, i.e. have 24 observations in the

On 08/17/2016 09:56 AM, Kaleb S. KEITHLEY wrote: > I propose to present on one or more of the following topics: > > * NFS-Ganesha Architecture, Roadmap, and Status,Jiffin Thotton copresenter. > * Architecture of the High Availability Solution for Ganesha and Samba > - detailed walk through and demo of current implementation > - difference between the current and storhaug

Hi Anton, I think it would be worth to remove this signature in the bottom line: Last modified: $Date: 2009/12/16 09:03:23 $ Otherwise, new people may think this page is long time abandoned :) Also, a question: may side projects that use LLVM enlist the mutually-beneficial tasks and add new categories? For example, we are interested specifically in Polly & GPU backend, plus some minor core

I''m getting 2 or three of these a day...Any ideas ? The 192.168.250.zz is a eth0:3 on a box that currently only has eth0:1 active Dec 1 15:47:40 machine-name kernel: Shorewall:all2all:REJECT:IN= OUT=eth0 SRC=my.real.ip.addr DST=66.228.216.22 LEN=68 TOS=0x00 PREC=0xC0 TTL=255 ID=12031 PROTO=ICMP TYPE=3 CODE=1 [SRC=66.228.216.22 DST=192.168.250.zz LEN=40 TOS=0x00 PREC=0x00 TTL=46

I have data that looks like O.lengthO.age 176 1 179 1 182 1 ... 493 5 494 5 514 5 606 5 462 6 491 6 537 6 553 6 432 7 522 7 625 8 661 8 687 10 704 10 615 12 (truncated) with a simple VonB growth model from within nls(): plot(O.length~O.age, data=OS) Oto = nls(O.length~Linf*(1-exp(-k*(O.age-t0))), data=OS, start=list(Linf=1000, k=0.1, t0=0.1), trace=TRUE) mod <- seq(0, 12)