similar to: superimpose density line over hist

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.

>>>>> On Tue, 31 Aug 1999 14:57, Werner Stahel <stahel@stat.math.ethz.ch> said: WSt> Here is a suggestion. It seems that qqplots, comparing a sample WSt> to a distribution other than the normal, are not explicitly WSt> available in S or R. I found (in S-plus / Trellis it is, see below) WSt> qqplot(y, rt(300, df = 5)) WSt> as an

Dear R community. I am using the identify() function to identify outliers in my dataset. This is the code I am using: #################################################################### # Function to allow identifying points in the QQ plot (by mouseclicking) qqInteractive <- function(..., IDENTIFY = TRUE) { qqplot(...) -> X abline(a=0,b=1) if(IDENTIFY) return(identify(X))

Full_Name: Madeleine Yeh Version: 1.9.1 OS: AIX 5.2 Submission from: (NULL) (151.121.225.1) After compiling R-1.9.1 on AIX 5.2 using the IBM cc compiler, I ran the checks. One of them failed. Here is the output from running the check solo. root@svweb:/fsapps/test/build/R/1.9.1/R-1.9.1/tests/Examples: ># ../../bin/R --vanilla < stats-Ex.R R : Copyright 2004, The R

Hi all. I am seeking for a statistical suggestion. My data set comprises 382 measures each having 169 variables. Each measure is the outcome of a nuclear magnetic resonance experiment, so each of the 169 points has the same unit. As I want to do some multivariate calibration using these data, I checked whether some multivariate outliers existed. I calculated Mahalanobis distances and did a

Hi, I'm trying to create a qqplot with reference to a Weibull distribution including a reference line. This is my current code: lights.data <- scan("lights.dat") #Generate Weibull quantiles prob.grid <- ppoints(length(lights.data)) prob.quant <- qweibull(prob.grid , 1.5,4) #Draw QQ plot qqplot(prob.quant,lights.data) #add red reference line qqline(lights.data,col = 2)

Dear Community, I want to identify outliers in my data. I don't know how to use identify command in the plots obtained. I've gone through help files and use mahalanobis example for my purpose: NormalMultivarianteComparefunc <- function(x) { Sx <- cov(x) D2 <- mahalanobis(x, colMeans(x), Sx) plot(density(D2, bw=.5), main="Squared Mahalanobis distances, n=nrow(x),

Hi! This is going to be a real newbie question, but I can't figure it out. I'm trying to plot densities of various functions of chi-square. A simple chi-square plot I can do with dchisq(). But e.g. chi.sq/degrees of freedom I only know how to do using density(rchisq()/df). For example: plot(1, type="n", xlab="", ylab="", xlim=c(0,2), ylim=c(0,7)) for (i

I am immediately reminded of something I read which goes "A sufficiently trained statistician can read the vagaries of a Q-Q plot like a sharman can read a chicken's entrails, with a similar recourse to scientific principles. Interpreting Q-Q plots is more a visceral than an intellectual exercise. The uninitiated are often mystified by the process. Experience is the key here."

Full_Name: Long Qu Version: 2.3.1 OS: Windows XP Submission from: (NULL) (64.113.93.235) The QQ-plot of two versions of simulating noncentral F-distributed random numbers has quite different scales: > qqplot(rf(1000,2,15,3),qf(runif(1000),2,15,3)) The rf() function reads: > rf function (n, df1, df2, ncp = 0) { if (ncp == 0) .Internal(rf(n, df1, df2)) else rchisq(n, df1,

Hello, I'm taking samples from certain distributions and drawing a density distribution over the histogram of the samples It works fine for the chi-square and for the normal, but not for the cauchy. Any idea what I'm doing wrong? Thanks x <- rchisq(10000, df = 4) hist(x, freq = FALSE, breaks=100) curve(dchisq(x, df = 4), col = 2, add = TRUE) x <- rnorm(10000) hist(x, freq =

Hello everyone I'm a beginner in Stats and R, I'm using R 2.10.1. I need to create a multivariate qq plot, there is 8 variable group with each has 55 number of input. An example of what I did so far, just to get my point out: > data=read.csv(file.choose(),header=T) > data country village group av_expen P2ary_ed no_fisher 1 Cook Islands Aitutaki D

Hi, I think I have identified a inaccuracy in dchisq when the non-centrality parameter is non-zero and large. Here's a little test: sys.dchisq.test <- function(N = 100000,mean = 0) { z <- rnorm(N,mean = mean, sd = 1) x <- z^2 xmin <- min(x) xmax <- max(x) br <- seq(xmin,xmax,length = 101) dbr <- br[2]-br[1] hist(x,br) p <- dchisq(br,df = 1,ncp =

Hi all, I've been trying to figure out how to superimpose a histogram on a biplot that shows the relative contribution of each axis. I have been using the NIPALS function (http://biomserv.univ-lyon1.fr/~dray/ files/softwares/nipals.R) to run principal component analyses. Here is a toy example. source("http://biomserv.univ-lyon1.fr/~dray/files/softwares/nipals.R")

Dear R users, I want to superimpose two graphs as well as ensure that they should have same scale with same x & y axis. I am using following command but it does not ensure same scale. *pdf(file = "../RESULTS/RS1.simulated.pdf", width = 10, height =6)* *plot(Reserves.RS, col = 1:2, screen = 1)* *par(new= TRUE)* *barplot(RS.active, axes = FALSE)* *dev.off()* * * Regards Vikram

Hi all, I have data which is represented as a histogram and want to add more data / another histogram to this plot using another color. That is I need to superimpose multiple histograms. But have no idea how to do this. Can anybody please give me a hint? Thanks, Andreas -- Andreas Wilm Institut fuer Physikalische Biologie Heinrich-Heine-Universitaet Duesseldorf

Dear R- experts, I am trying to superimpose two or more scatterplot matrices generated by pairs() to visualize the differences over each datasets, but have not been very successful. Two data frames, df1 and df2 for example, each has the same five variables in columns. My goal is to paint each dataset with a color on the same plot panel for each pair of the five variables. That is, in this

Hi r-users,   I try to draw histogram (in terms of probabilty) and superimpose with the gamma pdf. Using this code below I can get the plots BUT the y scale for the density is out of scale.  How do I change the y-axis scale to max 1?  Another thing, how I do draw smooth line rather that points?   Nota that my observed data is hume_pos and the fitted data is rgam1.   hist(hume_pos,prob=TRUE)

Dear list, I just tried to do the same thing, and did not find anything on a weighted qqplot. My weights are actually counts (positive integers). Here is a modification of qqplot, following Duncan Murdoch's suggestion. Any feedback would be welcome! Thanks, Jean-Christophe weighted.qqplot <- function (x, y, plot.it = TRUE, xlab = deparse(substitute(x)), ylab = deparse(substitute(y)),

NCSS has a nice plot of the histogram and density plot superimposed. The S-PLUS 4 Guide to Statistics on page 45 suggests the following code for a general purpose density plot for a vector named data iqd <- summary(data)[5]-summary(data)[2] plot(density(data,width=2*iqd),xlab="x",ylab="",type="l") Is it possible to superimpose the density plot on a histogram