similar to: find the mode of a dataset

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

Hi all, I think this question could be quite trivial, but I can?t find out the solution... How can you compute the statistic "mode" of a sample, in case it exists (as mode() returns the mode of an object)? I tried help.search("mode") but I couldn't find a clue... Any help would be much appreciated. Regards, Aurora

Hi, I have a large amount of data that I would like to create a histogram of and plot and do things with in R. It is pretty much impossible to read the data into R, so I have written a program to bin the data and now have a list of counts in each bin. Is it possible to somehow import this into R and use hist(), so I can, for instance, plot the probability density? I have looked at the help page

Using R-2.12.1 and latticeExtra-0.6-14, I would like to understand why a rootogram displaying samples from the Poisson distribution looks like I expected it, whereas a rootogram using the normal distribution does not: library(latticeExtra) rootogram(~rpois(1000, lambda = 50), dfun = function(x) dpois(x, lambda = 50)) rootogram(~rnorm(1000), dfun = function(x) dnorm(x,mean(x),sd(x))) I

Dear Masters, I have a question to submit consider the following script m<-4.95 obs<-rpois(36,m) # i generate 36 realization from a poisson(m) hist(obs,freq=F) curve(dpois(x,m),add=T,col="red") #i wish to overlay on the histogram the theorical poisson density function errors are returned saing the x vector doesn't contain integers.... really bizarre i can't give

The R poisson random generator rpois appears to have a bug for theta 10 or larger. The sample mean of the pseudo variates is too small: sample mean approx theta - 0.5. I use Version 1.1.1 (August 15, 2000) Of R on a Dell OptiPlex computer with the Windows XP Professional operating system. Has this bug been fixed in later versions? (I found another reported rpois bug, but it appears to be

Dear All, I have a massive dataset from which I would like to draw a histogram. Any ideas on how to accomplish this? Thanks in advance, Paul

Hi, I'm completely new to R, I am all at sea with the interface and the confusing help files, so would appreciate some help to do a simple task. Need to present the mean and variance of 100 different samples of poisson distributions (N=1000, with fixed lambda) in a file in two columnns, and then produce histograms. So far I have figured out: > N <- 1000 > x <- rpois(N, 3.1) ,

I issue the following: > d <- density(rnorm(1000)) > d and get: Call: density.default(x = rnorm(1000)) Data: rnorm(1000) (1000 obs.); Bandwidth 'bw' = 0.2235 x y Min. :-3.5157 Min. :2.416e-05 1st Qu.:-1.6892 1st Qu.:1.129e-02 Median : 0.1373 Median :7.267e-02 Mean : 0.1373 Mean :1.367e-01 3rd Qu.: 1.9639

Full_Name: Dr. Bernd Winkler Version: 1.2.2 OS: Linux Submission from: (NULL) (194.59.179.176) Hi all, having updated to version 1.2.2 last week I experienced some strange behaviour of the hist function. I want to plot a histogram of frequencies resp. counts, for example poisson random numbers, on a predefined and fixed x scale > hist(rpois(500, 2), breaks=0:10) But instead of the

Dear R-Gurus, I wonder why 'density' values as shown in hist or plot(density(x)) are sometimes over 1. How can that be? Example >hist(rnorm(1000,sd=.5),freq=FALSE) The resulting plot shows density values below 1 on the y-axis. However, >hist(rnorm(1000,sd=.1),freq=FALSE) shows density values over 1. How to interpret density values over 1? Greetings, Johannes

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, I have a couple of observations, a question or two, and perhaps a suggestion related to the plotting of density on the y-axis within the hist() function when freq=FALSE. I was using the function and trying to develop an intuitive understanding of what the density is telling me. After reading through this fairly helpful post:

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.

thanks to all for the 2d scatter plot. i have one more. how do i plot 'hist(y1, col="red") and hist(y2,col="blue") in the same window? thanks again.

Hi, I am new to R...a recent convert from SAS. I have a dataset that looks like this: SEQ A1 A2 A 532.5 554.5 B 25.5 35.5 C 265.2 522.2 D 245.55 521.56 E 546.52 141.52 F 243.25 32.56 G 452.55 635.56 H 15.14 16.54 I 543.4 646.56 J 54.4 654.5 K 646.5 64.54 L 645.4 614.46 M 646.54 634.46 I want to make a histogram

Hello all: I'm sure this is a trivial request, but I'm still a beginner at this, and haven't been able to find it. I need to create simulated data based on some empirical distributions of a single variable. I've found R functions to help me simulate data based on analytical distributions, or to make simulations based on correlation matrices, but nothing so simple as what I need.

Hello, all; I get an unexpected result when trying to plot a probability histogram with R1.9.1 on windows xp: #with the following code: > x <- runif(100,0,1) > hist(x) > hist(x, freq=F) > h <- hist(x, freq=F) > summary(h) # Length Class Mode #breaks 11 -none- numeric #counts 10 -none- numeric #intensities 10 -none- numeric #density 10

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]

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