similar to: Unsqueezing Stacked Figures

Hi all, I've tried to plot a vector which has two peaks in the density. This link shows the figure. http://docs.google.com/View?docid=dcvdrfrh_1dk9r2rc7 The red line is normal curve and green line is gamma curve. Notice that red line can correctly fit the histogram that has two peaks (i.e. red curve also has two peaks). But the gamma curve there only has one curve. Is there a way I can

Hi, With the following codes, I attempt to convert the data.frame into a matrix. However I notice that data.matrix function doesn't seem to work. __ BEGIN__ dat <- read.table("mydata", comment.char = "!" , na.strings = "null"); # Select n-genes by random sample # n = 1 nosamp <- 1 geneid <- sequence(nrow(dat)) geneid.samp <- sample(geneid,nosamp)

Dear experts, I tried to put the two plots into one final PNG figure with the following script. However instead of giving 2 plots in one figure, it only gives the the last plot in one figure. What's wrong with my script below? __BEGIN__ in_fname <- paste("mydata.txt.",sep="") out_fname <- paste("finalplot.png",sep="") dat <-

Hi, How can I partitioned an example vector like this > print(myvector) [1] 30.9 60.1 70.0 73.0 75.0 83.9 93.1 97.6 98.8 113.9 into the following pairwise partition: PAIR1 part1 = 30.9 part2 = 60.1 70.0 73.0 75.0 83.9 93.1 97.6 98.8 113.9 PAIR2 part1 = 30.9 60.1 part2 = 70.0 73.0 75.0 83.9 93.1 97.6 98.8 113.9 .... PAIR9 part1 = 30.9

Hi there, After being extremely impressed from implementing it in some customer installations, I've decided to migrate our mail infrastructure to dovecot. Being able to have /bin/checkpassword support across the board for pop, imap, and smtp authentication, as well as being able to ditch stunnel for the SSL layer...where were you in 2001?!? :) I have two concerns, the first is about the

Dear all, For example I want to process set of files. Typically Perl's idiom would be: __BEGIN__ @files = glob("/mydir/*.txt"); foreach my $file (@files) { # process the file } __END__ What's the R's way to do that? - Gundala Viswanath Jakarta - Indonesia

Hi all, I have the following data in which I want to parse and store them in a list __DATA__ > print(comp.ll) [1] "\tGene 11340 211952_at RANBP5 k= 1 LL= -970.692 " [2] "\tGene 11340 211952_at RANBP5 k= 2 LL= -965.35 " [3] "\tGene 11340 211952_at RANBP5 k= 3 LL= -963.669 " [4] "\tGene 12682 213301_x_at TRIM24 k= 1 LL= -948.527 "

Hi, I'm a bit puzzled by the gamlss fitting of exponential and lognormal data. Gamlss seems to think that exponentially distributed data fits better with a lognormal distribution, and vice versa. For example, X <- rexp(1000) Gexp <- gamlss(X~1,family=EXP) # X~1 is X tilde 1 GAMLSS-RS iteration 1: Global Deviance = 2037.825 GAMLSS-RS iteration 2: Global Deviance = 2037.825 Glno

Hi, Currently I have a density plot generated with this snippet. Is there a way I can add a line curve on top of it? I mean in one figure __BEGIN__ myhist <- hist(x col="blue", main = "Density Plot", xlab = "Exp Level", ) __END__ - Gundala Viswanath Jakarta - Indonesia

Hi all, I have the following named list: > print(y) $`200052_s_at` [1] -1066.975 -1063.893 -1062.815 -1062.121 -1059.004 $`200071_at` [1] -959.823 -953.980 -953.886 -948.781 -974.890 $`200084_at` [1] -1135.804 -1132.863 -1128.197 -1128.633 -1125.890 What I want to do is to iterate this name list and process its members. To do that I attempt the following code (but failed): __BEGIN__ ny

HI I use dovecot-1.0.r17 on FreeBSD scat.setcom 6.2-RELEASE. Recently authentification stop working. May 10 02:56:02 scat dovecot: auth(default): passwd(test,127.0.0.1): unknown user May 10 02:56:02 scat dovecot: auth(default): client out: OK 1 user=test User= &:/home/test:/tmp/email/bin/nonexistance= May 10 02:56:02 scat dovecot: auth(default): master in: REQUEST 23 43856 1

Dear all, I found that printing with 'cat' is very slow. For example in my machine this snippet __BEGIN__ # I need to resolve to use this type of loop. # because using write(), I need to create a matrix which # consumes so much memory. Note that "foo, bar, qux" object # is already very large (>2Gb) for ( s in 1:length(x) ) {

Dear all, In general practice one would slurp the whole file using this method before processing the data: dat <- read.table(filename) or variations of it. Is there a way we can access the file line by line without slurping/storing them into object? I am thinking something like this in Perl: __BEGIN__ open INFILE, '<' , 'filename.txt' or die $!; while (<INFILE>) {

Hi, Suppose I have the following data frame. __BEGIN__ > library(MASS) > data(crabs) > crab.pca <- prcomp(crabs[,4:8],retx=TRUE) > crab.pca$rotation PC1 PC2 PC3 PC4 PC5 FL 0.2889810 0.3232500 -0.5071698 0.7342907 0.1248816 RW 0.1972824 0.8647159 0.4141356 -0.1483092 -0.1408623 CL 0.5993986 -0.1982263 -0.1753299 -0.1435941 -0.7416656 CW

Hi all, I have a function - let's call it "myfunction". This function is based on some random number generator. Now, once in a while the function will break/crash depending on the random number it generate inside the function. To avoid the problem, what I intend to do is the following: 1. Catch the try-error using class. 2. Redo the function if it returns "try-error" 3.

Hi, I have the following dataset (simplified for example). __DATA__ 300.35 200.25 104.30 22.00 31.12 89.99 444.50 22.10 43.00 22.10 200.55 66.77 Now from that I wish to do the following: 1. Compute variance of each row 2. Pick top-2 row with highest variance 3. Store those selected rows for further processing To achieve this, I tried to: a) read the table and compute variance for each row,

I want to calculate the "scat" etc, values for each level of id, output a vector of these values that is a <- c(scat, sdog, srat, sbat ) and do an rbind on them. Each level of id has a different value of rate. So far it it looks to me like I can do this by a series of repeated subsets of Df butI would think that I should be able to do this with a function but I am not having

Hi all, How can we use ks.test() to evaluate goodness of fit of mixtures of distributions? For example I have the following dataset: > x [1] 176.1 176.8 259.6 171.6 90.0 234.3 145.7 113.7 105.9 176.2 168.9 136.1 [13] 109.2 110.3 164.3 117.7 131.3 163.7 200.4 196.4 196.2 168.6 190.4 127.5 [25] 136.0 114.2 112.0 91.9 333.4 295.5 172.0 293.3 91.7 289.7 118.8 55.1 [37] 161.9 233.9 197.7

Dear all, I have the following code that try to plot simple sinus curve into 2x2 grid in 1 page. But this code of mine create 4 plots in 1 page each. What's wrong with my approach? __BEGIN__ library(lattice) library(grid) test.plot <- function(x,y) { pushViewport(viewport(layout.pos.col=x, layout.pos.row=y)) pushViewport(viewport(width=0.6, height=0.6)); plot(sin,-pi,2*pi, main=

Dear all, Does R has any function/package that can pack and unpack string into bit size? The reason I want to do this in R is that R has much more native statistical function than Perl. Yet the data I need to process is so large that it required me to compress it into smaller unit -> process it -> finally recover them back again into string with new information. In Perl the