similar to: FINDNEXT problem, w2k and linux smbfs

Hello, I am trying to implement a formula aij= transition from state S_i to S_j/no of transition at state S_i Code I have written is working with three state {1,2,3 }, but if the number of states become={1,2,3,4,......n} then the code will not work, so can some help me with this. For and some rows of my data frame look like

Hi, I have two data sets look like below: ========================== state count1 percent1 CA 19 0.34 TX 22 0.35 FL 11 0.24 OR 34 0.42 GA 52 0.62 MN 12 0.17 NC 19 0.34 state count2 percent2 FL 22 0.35 MN 22 0.35 CA 11 0.24 TX 52 0.62 ========================== How to combine these two data set and make it look like below?

Hi, I think you overthought this one a little bit, I don't know if this is the kind of code you are expecting but I came up with something like that: generate_transition_matrix <- function(data, n_states) { #To be sure I imagine you should check n_states is right at this point transitions <- matrix(0, n_states, n_states) #we could improve a little bit here because at

I'm stuck on a seemingly simple problem. I'm trying to subset the data by several numbers and it cuts out half of the rows. Here is the sample code: test <- as.matrix(c(1,1,1,1,3,3,7,7,7,7)) Count <- tapply(test[,1], test[,1], length) # count for each value spp <- unique(test[,1]) Count1 <- as.data.frame(cbind(Count,spp)) Max <- max(Count) Count1$sppMax <-

Hi to all, I have this dataframe (I show the first six rows) >head(table) A R Fold.Change P.Value Count1 Count2 1 ENSRNOE00000000002_at 0 1.13 0.60 1 1 2 ENSRNOE00000000009_at 0 -1.04 0.73 3 3 3 ENSRNOE00000000020_at 0 -1.08

R-users, I have been using R for about 1 year, and I have run across a couple of graphics problem that I am not quite sure how to address. I have read up on the email threads regarding the differences between density and relative frequencies (count/sum(count) on the R list, and I am hoping that someone could provide me with some advice/comments concerning my approach. I will admit

Hello: I have been looking into projects that will automatically restrict hacking attempts on my servers running CentOS 5. I think the two top contenders are: DenyHosts - http://denyhosts.sourceforge.net Fail2ban - http://www.fail2ban.org >From what I see, DenyHosts only blocks based on failed SSH attempts whereas Fail2ban blocks failed attempts for other access as well. The main benefit

Dear all, I have some network data - about 300 vertices and several thousand edges. I am looking for a way to turn multiple edges into weights of the edges. I looked around and - surprisingly? - haven't found anything. Is there an easy way to do this? Best, Jonas [[alternative HTML version deleted]]

Dear colleagues, I have extracted the dates of several news stories from a newspaper data base to chart coverage trends of an issue over time. They are in a data frame that looks just like one generated by the reproducible code below. I can already generate a histogram of the dates with various intervals (months, quarters, weeks years) using hist.Date. However, there are two other

Hi R-users, I have a data set like this (first ten rows): id patient_id date code class eala ID1564262 1562 6.4.2006 12:00 5555 1 NA ID1564262 1562 6.4.2006 12:00 5555 1 NA ID1564264 1365 14.2.2006 14:35 5555 1 50 ID1564265 1342 7.4.2006 14:30 2222 2 50 ID1564266 1648 7.4.200614:30 2222 2 50 ID1564267 1263 10.2.2006 15:45 2222 2 10 ID1564267 1263 10.2.200615:45 3333 3 10 ID1564269 5646

I'm trying to create a histogram from the following code, but my data keeps adding the Num vector and plotting that. My data in the CSV file is just one vector. Does anyone know why? Thanks Conrad SPXdf = data.frame(read.csv(file = "SPX.csv", header = TRUE, sep = ",", dec = ".", fill = TRUE)) Max = max(SPXdf[,2]) Min = min(SPXdf[,2]) Count =

Having implemented a GC for HLVM, I am now turning my attention to implementing a GC that supports parallelism. To do this, I would like to use atomic instructions as well as mutexes. What is the status of LLVM's atomic instrinsics (e.g. CAS)? Is anyone using them in real projects? I realised that an obvious test would be to compile some simple example programs with llvm-g++ instead of

Hi ocfs2 developers, there are some news about the schedule for a new ocfs2 release that solve the actual bug/limitations? I can see an 1.4.7 release tagged here: http://oss.oracle.com/git/?p=ocfs2-1.4.git;a=summary Is there a planned release date? in my environment (about 5000000 files with 300000 new files/deletion per day) I see load until 1000 and I/O almost blocked for some hours of the

Ok, I assumed you wanted to compute a matrix M for all states such that M[i][j]= transition from state i to state j / number of transition from state i but from what you just answered it looks like you want to compute a matrix M for a set of states S such that: M[S_i][S_j]= transition from state S_i to state S_j / number of transition from state S_i where S_i is in the set S ? 2017-08-28

#I have a dataset with two factor. I want to combine those factors into a single factor and count the number of data values for each new factor. The following gives a comparable dataframe: a <- rep(c("a", "b"), c(6,6)) b <- rep(c("c", "d"), c(6,6)) df <- data.frame(f1=a, f2=b, d=rnorm(12)) df # I use the 'interaction' function to combine

hie Im trying to calculate the power of the logrank test for different values of rho .I was just wandering whether the following programme would do it. any suggestions are welcome s=50 number=1 count1=0;count2=0;count3=0;count4=0;count5=0;count6=0;count7=0;count7=0; count8=0;count9=0 while(s!=0){ n=20 n1=n/2

Chuck (Is it fine to call you Chuck?) has far more R jutsu than I do obviously. I don't know much about pmin and factor but it might worth looking into if you want to manipulate states by names (I assume this is why one might want to use it?) generate_transition_matrix <- function(data, states) prop.table(table(head(data, -1), tail(data, -1)), 1)[states,]

my program given below can some one make it presentable. I trying to simulate survival data and calculate the power. I think i could have done better. s=10 number=0 count1=0;count2=0;count3=0;count4=0;count5=0;count6=0;count7=0;count8=0; count9=0; count11=0;count22=0;count33=0;count44=0;count55=0;count66=0;count77=0; count88=0;count99=0; while(s!=0){ n=100 n1=n/2 n2=n/4

HI Elisa, You could use ?cut() vec1<-c(33,18,13,47,30,10,6,21,39,25,40,29,14,16,44,1,41,4,15,20,46,32,38,5,31,12,48,27,36,24,34,2,35,11,42,9,8,7,26,22,43,17,19,28,23,3,49,37,50,45) label1<-unlist(lapply(mapply(c,lapply(seq(0,45,5),function(x) x),lapply(seq(5,50,5),function(x) x),SIMPLIFY=FALSE),function(i) paste(i[1],"<x<=",i[2],sep="")))

Dear R-users, I've searched for an answer to my question, but so far haven't been able to find a solution. Its likely a simple issue, but have no idea how to do this. A simplified version my (very large) data set looks like this: > > bugs FRUIT SEED_ID SURVIVE 1 1 A 1 2 1 B 1 3 1 C 1 4 1 D 0 5 1 E