similar to: trouble with histograms

Hi I have data for events in rows, with columns for person and date. Each person may have more than one event; tC <- textConnection(" Person date bob 1/1/00 bob 1/2/00 bob 1/3/00 dave 1/7/00 dave 1/8/00 dave 1/10/00 kevin 1/2/00 kevin 1/3/00 kevin 1/4/00 ") data <- read.table(header=TRUE, tC) close.connection(tC) rm(tC) I would like to add a new column to my dataframe containing

Hello, I have longitudinal data of the form below from N subjects; I am trying to create figure with N small subplots on a single page, in which each plot is from only one subject, and in each plot there is a separate curve for each value of param1. So in this case, there would be four plots on the page (one each for Bob, Steve, Kevin and Dave), and each plot would have two separate curves (one

Hi Guys, stumped by a simple problem. I would like to take a file of the form Pair group param1 1 D 10 1 D 10 1 R 10 1 D 10 2 D 10 2 D 10 2 D 10 2 R 10 2 R 10 etc.. and for each pair, calculate the average of

> >>>>> "PD" == Peter Dalgaard BSA <p.dalgaard at biostat.ku.dk> writes: > > PD> "Venables, Bill (CMIS, Cleveland)" <Bill.Venables at cmis.CSIRO.AU> > PD> writes: > >> The fact that every elementary book on statistics does it this way > >> does not make it correct. To be helpful, a histogram really

Hi all, I have a short R code file that I am using to perform calculations on a dataset. I am having a few issues with output: 1. Although my input data file is 2149 lines long, when I type "results.df" from the command line, I get the appropriate calculation results for only the first 46 rows. Same result if I "sink" the output to a file, and type "results.df" at

Hi, I have a set of observations which are divided into two sets A and B. I have some code that bins the dataset into 10 bins based on the max and min of the observed values. I would like to make a histogram of A & B using my calculated bins but plot the distribution of B on top of A (like a stacked barplot). This is possible since both sets A & B are binned using the same bin ranges.

I spent some time on this simple question, also searched the forum, eventually hacked my way to an ugly solution for my particular problem but I would like to improve my coding: I have data of the form: df <- expand.grid(group=c('copper', 'zinc', 'aluminum', 'nickel'), condition1=c(1:4)) I would like to add a new data column "condition2", with values

I have what is probably a simple problem. I have a data file from an MCMC Bayes estimation problem that is a vector of 500,000 numeric values (just one variable) ranging from 100,000 to 700,000. I need to display the histogram of this data in a high quality graphic for a figure in a journal publication. I want 100 bins so as to display a reasonable complete and smooth histogram, and I need the

HI everyone, I'm plotting a histogram in R and within that histogram i need to demonstrate the percentage of another variable (Percentage of MutStatus) within the bins plotted inthe histogram....I don't know how to do that! Data:Validation_Status Mutation_Status TvarRatio Wildtype None 0.08 Wildtype None 0.08 Wildtype None 0.08 Wildtype None 0.08 Wildtype None 0.080139373 Wildtype None

Dear List, I have a set of distributions recorded at an equal interval of time and I would like to plot them as series of horizontal histograms (with the x-axis representing time, and y-axis representing the bins) since the distribution shifts from unimodal to multimodal in several occasions. What I would like to see is something close to a violinplot, but I do not want a kernel density

Hello all, I have a peculiar and particular bug that I stumbled across with ggplot2. I cannot seem to replicate it with anything other than my specific data set. Here is the problem: - when I try to plot a histogram, allowing for ggplot2 to decide the binwidths itself, I get the following error: - stat_bin: binwidth defaulted to range/30. Use 'binwidth = x' to

Hello I'm doing some experiments with the various histogram functions and I have a two questions about the "prob" option and binning. First, here's a simple plot of my data using the default hist() function: > hist(data[,1], prob = TRUE, xlim = c(0, 35)) http://go.sneakymustard.com/tmp/hist.jpg My first question is regarding the resulting plot from hist.scott() and

I have a dataset of the form below, consisting of one unique ID per row, followed by a series of visit dates. At each visit there are values for 3 dichotomous variables. Of the 8 different possible combinations of the three variables, 4 are "abnormal" and the remaining 4 are "normal". Everyone starts out abnormal, and then either continues to be abnormal at subsequent visits,

Rhelpers: I'm curious what the appropriate analysis to use for testing the hypothesis that two histograms are statistically different from one another? Thanks! --j

Hi, Short Version: Is there a function to re-bin a histogram to new, broader bins? Long version: I'm trying to create a histogram, however my input-data is itself in the form of a fine-grained histogram, i.e. numbers of counts in regular one-second bins. I want to produce a histogram of, say, 10-minute bins (though possibly irregular bins also). I suppose I could re-create a data set as

I woud like to plot cumulative histograms. Specifically, I have data like Sex M M F M F F M F Height 6 6.3 6.1 5.5 7.2 6.2 5.9 6.0 .... and I want to plot a histogram of the distribution of all heights, colouring the histogram bars according to sex, for example | o | oo o | o oo ** o o = observations of women | o o*o***o * = observations of

I'm trying to add the exact value on top of each column of an Histogram, i have been trying with the text function but it doesn't work. The problem is that the program it self decides the exact value to give to each column, and ther is not like in a bar-plot that I know exactly which values are been plotting. If anyone have any new idea on how to do this Thanks Matias -- View this

Hello, I am new to R and am having difficulty formatting numerical output from a regression analysis. My code iteratively performs linear regression on a dataset while excluding certain data ranges. My code: rm(list = ls(all = TRUE)) sink("outfile") dat <- read.table("testdat", sep="\t", header=TRUE) int = 0.2 for (x in c(0:20)) { subdat <- subset(dat, time

Hi, Apology for this question being off the topic (OT) of R, though I expect this list might be the best place on the net to ask this question. In brief, the question is: what classification algorithm can one use if the features are histograms? I have a classification problem, and believe that histograms of the distribution of some values may be the best "feature" to use. To

this is the command i made for a normal distribution, but when i try to plot the histograms, i dont know why the bars don't stick on the line... nsamples<-1000 sampsize<-15 Samples<-matrix(rnorm(nsamples*sampsize,0,1),nrow=nsamples) a<-apply(Samples,1,var) NC14<-a*14 x<-0:40 plot(x,dchisq(x,14),type='h') hist(NC14,freq=F,add=T) -- View this message in context: