similar to: Joining Histograms Into a Figure

I am creating a side-by-side histogram using "multhist" of PLOTRIX. However, I can't seem to control the X-axis. It yields the following X points in the axis: 1 3 5 7 9 13 17 21 25 29 33 with uneven spacing between x-ticks (see attached file). Especially I want to create a bar for every x-axis (1,2,3,4...36), now not every x-axis has a bar. Is there a way to alter my following

Hi, I have this string, in which I want to extract some of it's element: > x <- "Best-K Gene 11340 211952_at RANBP5 Noc= 3 - 2 LL= -963.669 -965.35" yielding this array [1] "211952_at" "RANBP5" "2" In Perl we would do it this way: __BEGIN__ my @needed =(); my $str = "Best-K Gene 11340 211952_at RANBP5 Noc= 3 - 2 LL= -963.669

Hi, Below I have a function mlogl_k, later it's called with "nlm" . __BEGIN__ vsamples<- c(14.7, 18.8, 14, 15.9, 9.7, 12.8) mlogl_k <- function( k_func, x_func, theta_func, samp) { tot_mll <- 0 for (comp in 1:k_func) { curr_mll <- (- sum(dgamma(samp, shape = x_func, scale=theta_func, log = TRUE))) tot_mll <- tot_mll + curr_mll }

Dear all, Currently I have the following output > mydensity <- density(x) > print(mydensity) x y Min. : -92.14 Min. :0.000e+00 1st Qu.: 356.66 1st Qu.:5.530e-09 Median : 805.45 Median :4.681e-05 Mean : 805.45 Mean :5.564e-04 3rd Qu.:1254.24 3rd Qu.:3.370e-04 Max. :1703.04 Max. :5.541e-03 How can I access the Max value of

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, I tried to compute maximum likelihood under gamma distribution, using nlm function. The code is this: __BEGIN__ vsamples<- c(103.9, 88.5, 242.9, 206.6, 175.7, 164.4) mlogl <- function(alpha, x) { if (length(alpha) > 1) stop("alpha must be scalar") if (alpha <= 0) stop("alpha must be positive") return(- sum(dgamma(x, shape = alpha, log = TRUE)))

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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, 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

How do you draw two histograms in one figure? Two separate uses of the "hist" function always produce two separate figures... Thanks, Roman -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in 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, 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)

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 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 "

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) ) {

Hi all, I am interested in performing a cluster analysis on ecological data from forests in Pennsylvania. I would like to develop definitions for forest types (red maple forests, upland oak forests, etc.(AH AR in attached table)) based on measured attributes in each forest type. To do this, I would like to 'draw clusters' around forest types based on information from various tree

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

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

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,

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>) {