similar to: histogram frequency weighing

Hello all! I have a problem with ggplot2 library. I want to do an heat map and the y variables are the year months. If I use the following code, he y values are in alphabetical order, but I want it in month order. The code is: library(reshape) library(ggplot2) library(scales) p <- ggplot(data.m, aes(variable, Month)) + geom_tile(aes(fill = value),

below is my data frame. I would like to compute summary statistics for mgl for each river mile (mean, median, mode). My apologies in advance- I would like to get something like the SAS print out of PROC Univariate. I have performed an ANOVA and a tukey LSD and I would just like the summary statistics. thanks stephen RM mgl 1 215 0.9285714 2 215 0.7352941 3 215 1.6455696 4 215

f <- (structure(list(X = structure(96:97, .Label = c("119DAmm", "119DN", "119DNN", "119DO", "119DOC", "119Flow", "119Nit", "119ON", "119OPhos", "119OrgP", "119Phos", "119TKN", "119TOC", "148DAmm", "148DN", "148DNN", "148DO",

Dear R-helpers, I have a question regarding LU-decomposition with function lu in package Matrix. The following simple example confuses me: Why is as.matrix(elu$U) not an upper triangular matrix? u3 <- matrix(c(1,1,1,1,1,1,-1,1,0,0,0,0,0,-1,1,0,0,0,-1,0,1,0,0,0,0,0,-1,1,0,0),5,6,byrow=T) elu <- expand(lu(Matrix(u3,sparse=F))) as.matrix(elu$U) I only have very limited experience with the

Dear All, I have to use loop over an array so I am using following procedure count<-1 repeat{ count<-count + 1 c(g[count],1:i[count]) ->qw if(count>5)break } as a result qw is [1] 0.9643836 1.0000000 2.0000000 3.0000000 4.0000000 5.0000000 [7] 6.0000000 7.0000000 8.0000000 9.0000000 10.0000000 11.0000000 [13] 12.0000000 13.0000000 14.0000000 15.0000000 16.0000000

Hello all R-users _question 1_ I need to make a statistical model and respective ANOVA table but I get distinct results for the T-test (in summary(lm.object) function) and the F-test (in anova(lm.object) ) shouldn't this two approach give me the same result, i.e to indicate the same significants terms in both tests??????? obs. The system has two restrictions: 1) sum( x_i ) = 1 2) sum(

folks, I have been struggling with the "R" documentation for too long now and I need a simple answer on two questions. The documentation does not have adequate examples. Please help. given two equal vector lists: A <- c(0,1,2,3) B <- c(5,6,7,8) [Question #1] how do I dump them to a text file with the following format:

Hi list, I have the following code to compute the acf of a time series acfresid <- acf(residfit), where residfit is the series when I type acfresid at the prompt the follwoing is displayed Autocorrelations of series ?residfit?, by lag 0.0000 0.0833 0.1667 0.2500 0.3333 0.4167 0.5000 0.5833 0.6667 0.7500 0.8333 1.000 -0.015 0.010 0.099 0.048 -0.014 -0.039 -0.019 0.040 0.018

Hello, When making a graph, plot and boxplot automatically sort my factor levels (y axis) into alphabetical order. Is there a way to make it NOT do this? I've tried: sort.by="none", sorted=FALSE, sort=FALSE, reorder=FALSE. Thank you.

Hi, I have a question about the computation of confidence intervals in the zyp package, in particular using the functions zyp.sen and confint.zyp, or zyp.yuepilon. (1) I'm a bit confused about the confidence intervals given by zyp.sen and confint.zyp. When I request a certain confidence interval in the function, the R output seems to deliver another confidence interval, e.g. when I set

I compiled R 2.1.0 under Windows XP SP2 as a preliminary to rebuilding a custom package for use with R 2.1.0. The compile completed successfully, and I was able to run demo(graphics) successfully. But make check and make check-recommended fail. > version _ platform i386-pc-mingw32 arch i386 os mingw32 system i386, mingw32 status major 2 minor 1.0 year 2005

is there a way to do element-by-element multiplication as in Gauss and MATLAB, as shown below? Thanks. --- a 1.0000000 2.0000000 3.0000000 x 1.0000000 2.0000000 3.0000000 2.0000000 4.0000000 6.0000000 3.0000000 6.0000000 9.0000000 a.*x 1.0000000 2.0000000 3.0000000 4.0000000

Dear R helpers: I have tried many times to find some way to read a list into R. But I faid. Here is an example: I have a file 'List.txt' which includes data as follows: [[1]] [1] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5 0.0 0.0 0.0 [19] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 [[2]] [1] 0.0000000 0.5000000 0.0000000 0.0000000

Hi All, In the script below, the importance measure for column 4 (ie MeanDecreaseGini) indicated "Inf" for V7. Running the getTree command showed that "V7" had been selected at least twice in one of the trees for Random Forest. So the "Inf" command was not generated as a result of dividing the sum of the decreases by 0. Any suggestions on what may be causing the

Hello, I am trying to get a linear model of y ~ log(x). *> lm (y~log(x))* However, I always get an error report: /Error in model.frame.default(formula = y ~ log(x), drop.unused.levels = TRUE) : variable lengths differ (found for 'log(x)')/ *Here was my y:* > y [1] 0.4500000 0.0500000 0.5000000 0.4000000 0.0000000 0.5000000 0.4000000 [8] 0.0500000

Dear list, I just made a very simple mistake, but it was hard to spot. And I think that I should warn other people, because it is probably so simple to make... === R code === # Let us create a matrix: (a <- cbind(c(0,1,1), rep(1,3))) # [,1] [,2] # [1,] 0 1 # [2,] 1 1 # [3,] 1 1 # That is a MISTAKE: a/colSums(a) # [,1] [,2] # [1,] 0.0000000 0.3333333

Dear all, I have two data frames- x1 and y1 with same row names and column names(actually the names of the patients). x1 a b c d e a 1.0000000 0.4730679 0.6226994 0.6036036 0.6433333 b 0.4730679 1.0000000 0.6227273 0.6303855 0.5730858 c 0.6226994 0.6227273 1.0000000 0.7290503 0.6900585 d 0.6036036 0.6303855 0.7290503 1.0000000

Hi, I am performing experiments in the field of visual perception where we often apply balanced designs. Within a group of normal subjects, we vary different stimulus conditions (like contrast, luminance, temporal frequency of stimulation) and derive some psychophysical or electrophysiological results from our subjects. Often, the main question is to test the effect of these parameters

Hello, I have 2 functions (a and b) a = function(n) { matrix (runif(n*2,0.0,1), n) } > > > b = function (m, matrix) { > n=nrow (matrix) > p=ceiling (n/m) > lapply (1:p, function (l,n,m) { > inf = ((l-1)*m)+1 > if (l<p) sup=((l-1)*m)+m > else sup=n >

Hi! I am studying differences between R and S-PLUS smooth() functions. I know from the help that they worked differently, so I ask: - exist a package that permit to have the same results? - alternatively, someone know how can I obtain the same results in R, using a self made script? I know that S-PLUS use the 4(3RSR)2H running median smoothing and I try to implement it with the code below. I