similar to: ploting an ellipse keeps giving errors

Hi, I'm using the R library(car) to draw confidence/prediction ellipses in a scatterplot. >From what i understood the ellipse() function return an ellipse based parameters: shape, center, radius . If i read dataEllipse() function i can see how these parameters are calculated for a confidence ellipse. ibrary(car) a=c(12,12,4,5,63,63,23) b=c(13,15,7,10,73,83,43) v <-

Hi: Does Ellipse and dataellipse function in R produce the same ellipse? I wanted to see how the radius for the Ellipse function in R calculated. Also what is the var-covariance matrix, if any, assumed for the dataellipse function? Heres an example of the code where I am generating Multivariate normal data and creating ellipse using the 2 functions: library(car) library(mvtnorm) mu =

Full_Name: Volker Franz Version: Version 1.6.2 (2003-01-10) OS: Debian Submission from: (NULL) (192.124.28.104) Hi there, it seems to me that data.ellipse of package "car" (Version 1.0-1) produces confidence interval's which are too big. To see this, do: library(car) plot(c(-2,2),c(-2,2),pch=0) data.ellipse(rnorm(10000),rnorm(10000),levels=0.68,plot.points=F) abline(v=+1)

I have empirical Bayes estimates for slopes and intercepts for a number of subjects and I would like to plot the slopes and intercepts with confidence ellipses. These ellipses would be based on the confidence intervals for the slope and intercepts (forming the major and minor axis of each ellipse), and the correlation in the slope and intercepts. The ellipse function in the car library

Is there a way to plot elliptical shapes? symbols() only provides circles... Thanks! Kamila

Dear list members, This might be a silly question but I just can't figure it out. I am using the "ellipse" package on covariance matrices. I would simply like to plot my ellipses WITH its two axis ploted as well. These axis represents the 2 eigen vectors of my matrix and it is important that I can graphically show them. Is there an easy way to do so? Many thanks, Antoine -- View

Dear all, I generated a Correlograms and used the panel.ellipse (confidence ellipse and smoothed line) option. Is there a way to get instead of the smoothed line the linear regression? Thanks, As hz -- View this message in context: http://r.789695.n4.nabble.com/Correlograms-and-linear-regression-tp2331071p2331071.html Sent from the R help mailing list archive at Nabble.com.

Dear R users, first I take this opportunity to greet all the R community for your continuous efforts. I wrote a function to calculate the pdf and cdf of a custom distribution (mixed gamma model). The function is the following: pmixedgamma3 <- function(y, shape1, rate1, shape2, rate2, prev) { density.function<-function(x) { shape1=shape1 rate1=rate1 shape2=shape2

Hi, sorry for repeating the question but this is kind of important to me and i don't know whom should i ask. So as noted before when I do a parameter fit to the beta distr i get: fitdist(vectNorm,"beta"); Fitting of the distribution ' beta ' by maximum likelihood Parameters: estimate Std. Error shape1 2.148779 0.1458042 shape2 810.067515 61.8608126 Warning

Hi , I am new to R. I am trying to run a simple R script as shown below: aov.R ------ data1<-c(49,47,46,47,48,47,41,46,43,47,46,45,48,46,47,45,49,44,44,45,42,45,45,40 ,49,46,47,45,49,45,41,43,44,46,45,40,45,43,44,45,48,46,40,45,40,45,47,40) matrix(data1, ncol= 4, dimnames = list(paste("subj", 1:12), c("Shape1.Color1", "Shape2.Color1", "Shape1.Color2",

Hi, Interpretation problem ! so what i did is by using the: >fit1 <- fitdist(vectNorm,"beta") Warning messages: 1: In dbeta(x, shape1, shape2, log) : NaNs produced 2: In dbeta(x, shape1, shape2, log) : NaNs produced 3: In dbeta(x, shape1, shape2, log) : NaNs produced 4: In dbeta(x, shape1, shape2, log) : NaNs produced 5: In dbeta(x, shape1, shape2, log) : NaNs produced 6: In

Buenos dias! Os escribo para ver si me podeis ayudar con un asunto en el que me he quedado un poco encallado. Lo que tengo que hacer es sacar los percentiles (0.001, 0.005, 0.95 y 0.999) de varias distribuciones beta, concretamente 418. Cada distribucion esta definida por los parametros "shape1" y "shape2". Por lo tanto tengo una base de datos de 418 filas y en cada una de

Hallo, I need your help. I fitted my distribution of data with beta-prime, I need now to plot the Cumulative distribution. For other distribution like Gamma is easy: x <- seq (0, 100, 0.5) plot(x,pgamma(x, shape, scale), type= "l", col="red") but what about beta-prime? In R it exists only pbeta which is intended only for the beta distribution (not beta-prime) This is

Dear all, I would like to draw a 3-D horizontal cylinder preferably in RGL device (because this gives the look from different angles). Basic idea is from http://www.tau.ac.il/cc/pages/docs/sas8/insight/chap18/sect3.htm. Below is the description exactly what I want to do. Please see at figure 18.6, 1st plot. Here it is an confidence ellipsoid. Suppose now you put another 4 same ellipsoids on top

Hello everyone I really need some help here. I made a confidence ellipse using the function ellipse from the package ellipse: ellipse(SD, centre=colMeans(pcsref),t=sqrt((p * (n-1)/(n-p))*qf(0.99, p,n-p)) Now, I want to write a function whom return TRUE or FALSE if a given observation is in the confidence ellipse. But I have no clue how to do it Can anyone help me? Best regards Jessica

Another solution: library("HelpersMG") plot(0:10,type="n",axes=FALSE,xlab="",ylab="", asp=1) ellipse(center.x = 3, center.y = 5, radius.x = 5, radius.y = 5, lwd=10, col=NA, border=rgb(red = 1, green = 0, blue=0, alpha = 0.5)) ellipse(center.x = 8, center.y = 5, radius.x = 5, radius.y = 5, lwd=10, col=NA, border=rgb(red = 0, green = 1, blue=0, alpha =

Hi, I drew an ellipse with the package ellipse. Now I would like to know if a point is inside the ellipse. Is any R functions to do it without computing the equation of the ellipse manually? Thanks. For example, if I do "plot(ellipse(0.8), type = 'l')", I would like to know if (0,1) belongs to the drawn ellipse. Regards, Alain -- Alain Guillet Statistician and Computer

I've discovered an infelicity (I guess) in qbeta(): it's not a bug, since there's a clear warning about lack of convergence of the numerical algorithm ("full precision may not have been achieved"). I can work around this, but I'm curious why it happens and whether there's a better workaround -- it doesn't seem to be in a particularly extreme corner of parameter

Hello, SAS' point and click interface has the option of produce a scatterplot with a superimposed confidence ellipse for the correlation coefficient. Since I generally like R so much better, I would like to reproduce this in R. I've been playing with the ellipse package. In order to have the points and the ellipse on the same graph I've done the following. (Load ellipse

Hi folks, I have a question about how to efficiently produce random numbers from Beta and Binomial distributions. For Beta distribution, suppose we have two shape vectors shape1 and shape2. I hope to generate a 10000 x 2 matrix X whose i th rwo is a sample from reta(2,shape1[i]mshape2[i]). Of course this can be done via loops: for(i in 1:10000) { X[i,]=rbeta(2,shape1[i],shape2[i]) } However,