similar to: density of hist(freq = FALSE) inversely affected by data magnitude

Hi list, After a lot of tweaking i have managed to create a histogram with an overlaying density plot. The histogram shows a sample of birth weights of babies and the density plot shows birth weights from a much larger reference populaton. My data is divided in 0.1 Kg bins so in the code below binweigh=0.1. The trouble with the current graph is that it is not very clear since the density plot

For the hist estimate >par(mex=1.3) >dens<-density(q) >options(scipen=4) > ylim<-range(dens$y) > h<-hist(q,breaks="scott",freq=FALSE,probability=TRUE, +? right=FALSE,xlim=c(9000,16000),ylim=ylim,main="Histogram of q(scott)") > lines(dens) >box() ? For the kernel estimate>options(scipen=4) > d <- density(q, bw =

Dear developers, the current implementation of hist.default() calculates 'density' (and 'intensities') as dens <- counts/(n*h) where h has been calculated before as h <- diff(fuzzybreaks) which results in 'fuzzy' values for the density, see e.g. > tmp <- hist(1:10,breaks=c(-2.5,2.5,7.5,12.5),plot=FALSE) > print(tmp$density,digits=15) [1]

Dear All, I am a undergraduate using R for the first time. It seems like an excellent program and one that I look forward to using a lot over the next few years, but I have hit a very basic problem that I can't solve. I want to produce a standardised histogram, i.e. one where the area under the graph is equal to 1. I look at the manual for the histogram function and find this: freq:

Hi I have recently been analyzing birthweight data from a clinic. The data has obvious defects in that there is digit preference on certain weights making them overrepresented. This shows as spikes in the histogram on certain well rounded weights like 2, 2.5, 3, etc. I would like to show this to government officials but can't figure out how I should present the finding in an easy to

Hi all, I'm trying to superimpose a rchisq density line over a histogram with something like: hist(alnlength) lines(density(rchisq(length(alnlength), 4)),col="red") But the rchisq line won't appear anywhere, Anyone knows what I am missing here? Thanks in advance, Albert.

Hi! Do not understand following behavior. > summary(test$dif) Min. 1st Qu. Median Mean 3rd Qu. Max. 0.7389 0.9713 0.9850 0.9818 1.0000 1.0000 length(test$dif) [1] 85879 tmp <- hist(test$dif,breaks=100,freq=FALSE) The density on the Y axis in the plot are in the range 0-200. Thought that the density should be in the range 0-1 (something like

There were some questions about hist() a couple of days ago which triggered this post. My question/suggestion is about the y-axis in hist. There are reasons to prefer making the y-axis density=relative frequency/bin width. One reason is that the height of the plot does not depend on the bin width; another is that if your histogram is in density then you can easily superimpose a smooth theoretical

Hi, This is a very basic question, but I would like to undestand hist(). I thought that the hist( , freq=FALSE) should provide the relative frequencies (probabilities), and so they should sum 1, however: set.seed(2) ah <- hist(rnorm(100), freq=F) sum(ah$intensities) [1] 2 set.seed(2) bh <- hist(rlnorm(100), freq=F) sum(bh$intensities) [1] 0.4999996 I'm getting similar figures with

In R0.61, In hist(), should the line rel.freqs <- counts/(sum(x) * diff(breaks)) computing the relative frequencies or height of the rectangles in a histogram not be rel.freqs <- counts/(sum(counts) * diff(breaks)) instead, or do I misunderstand something? Thanks, Philippe -- -------------------------------------------------------- Philippe Lambert Tel:

Hi all, A friend send me a question on why does this: x<-rpois(100,1) sum( hist(x)$density ) Gives out "2" I tried this: sum( hist(x, freq =T)$density ) It didn't help. Then he came back with the following insight: # with breaks b<-c(0,0.9,1:8) sum(hist(x,breaks=b)$density) # Much more then 2 # but if we add weights according to the interval length

Hello! Up to now I have been using hist() to display the distributions. Howevere, I noteiced strange numbers on y (vertical) axis, if I used probability = T or freq = F option. I thought it is a bug and launched the R-bug system and found some posts on that matter. Brian Ripley responded to one, that one should look at truehist() for that. Ok I can use truehist() if I want to see the ratios

Hi, I have a casting/formatting question on hist.POSIXt: The histogram plot from POSIXct works perfect (with help of Prof. Ripley -thanks!). When processing the hist(plot=FALSE) output and then plotting the results over the x-axis (bins) coming from hist(), I lose the date/time labels, getting instead integers displayed. Trying to cast the $breaks with as.POSIXct gives silly results with

Dear listers, A quick question about breaks in hist(). The histogram is highly screwed to the right, say, the range of the vector is [0, 2], but 95% of the value is squeezed in the interval (0.01, 0.2). My question is : how to set the breaks then make the histogram look even? Thanks in advance, Leaf

> x = rnorm(100) > b = seq(min(x) - 1, max(x) + 1, length = 11) > b [1] -3.4038769 -2.7451072 -2.0863375 -1.4275678 -0.7687980 -0.1100283 [7] 0.5487414 1.2075111 1.8662808 2.5250506 3.1838203 > > invisible(hist(x, breaks = b, include.lowest = TRUE, plot = FALSE)) Warning message: argument 'include.lowest' is not made use of in: hist.default(x, breaks = b,

Hello, I have a problem with the hist() function and showing densities. The densities sum to 50 and not to 1! I use R version 2.9.1 (2009-06-26) and I load the seqinR library. My data is the following vector: [1] 0.1400000 0.2000000 0.2200000 0.2828283 0.1600000 0.1600000 0.3600000 [8] 0.1600000 0.2200000 0.2600000 0.2000000 0.3000000 0.2200000 0.2342342 [15] 0.1800000 0.2200000 0.1600000

Dear all, I have a surprising problem with the representation of frequencies in a histogram. Consider, for example, the R code: b<-rnorm(2000,3.5,0.3) hist(b,freq=F) When I plotted the histogram, I expected that values in the y-axis (the probability) varied between 0 and 1. Instead, they varied within the range 0-1.3. Have you got any suggestion for obtaining a correct graph with

It is not really a bug but a strange choice. When the option freq=F chosen, hist should plot relative frequency. It plots proportional to relative frequency by the factor of bin width. Is there a reason for this? A more normal choice seems to be to have it independent of the bin width. Yash Mittal University of Arizona ---------------------------------------------------------------- This

Dear R People: Here is yet another histogram question (yahq), please: When I use the hist() command with freq=F, I get density on the side. I would really like to have relative frequency; that is, Rf = density/(sum(density)) Is there a step that I'm leaving out, please? thanks! Sincerely, Erin hodgess at uhddx01.dt.uh.edu

Hi all, I'm looking to add a "density" smoother on top of a hist when Freq=T. In order to do this I can use the relation between count and density, but I would like to know if there is a way for me to predict it upfront. Here is an example: set.seed(242) z = rnorm(30) hist_z <- hist(z) hist_z$counts / hist_z$density # the relation is 15 # why is this 15 ?? # So I can now do: