similar to: Multivariate kernel density estimation

This may be a begining question. If so, please bear with me. If I have some data that based on the historgram and other plots it "looks" like a beta distribution. Is there a function or functions within R to help me determine the model parameters for such a distirbution? Similarily for other "common" distirbutions, Poisson(lambda), Chi-Square(degrees of freedom, chi-square

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

I am having a hard time interpreting the results of the 'shapiro.test' for normality. If I do ?shapiro.test I see two examples using rnorm and runif. When I run the test using rnorm I get a wide variation of results. Most of this may be from variability of rnorm, samll sample size (limited to 5000 for the test), etc but if I repeat the test multiple times I can get: >

I'm having trouble figuring out how to create a function using "body<-" (). The help file for body() says that the argument should be a list of R expressions. However if I try that I get an error: > tmpfun <- function(a, b=2){} > body(tmpfun) <- list(expression(z <- a + b),expression(z^2)) Error in as.function.default(c(formals(f), value), envir) :

Fix DRM_REFELCT_Y -> DRM_REFLECT_Y. Signed-off-by: Robert Foss <robert.foss at collabora.com> --- drivers/gpu/drm/drm_blend.c | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/drivers/gpu/drm/drm_blend.c b/drivers/gpu/drm/drm_blend.c index a0d0d6843288..dee67ef6c670 100644 --- a/drivers/gpu/drm/drm_blend.c +++ b/drivers/gpu/drm/drm_blend.c @@ -129,7 +129,7 @@ *

Dear R users: Recently, I tried to write a program to calculate cross-validated predicted value. My sources are as follows. However, the R reported an error. Could you please check the sources? Thanks. set.seed(100) x<-rnorm(100) y<-sample(rep(0:1,50),replace=T) dat<-data.frame(x,y) library(rms) fito<-lrm(y~x) preo<-predict(fito) pre<-matrix(NA,nrow=100,ncol=200) for (i in

Add DRM_MODE_ROTATE_ and DRM_MODE_REFLECT_ defines to the UAPI as a convenience. Ideally the DRM_ROTATE_ and DRM_REFLECT_ property ids are looked up through the atomic API, but realizing that userspace is likely to take shortcuts and assume that the enum values are what is sent over the wire. As a result these defines are provided purely as a convenience to userspace applications.

Hi All, I would like to fill the area under a curve with a gradient of colors. Are there any packages or trick I could use Thanks Stefan Stefan Van Dongen Antwerp [[alternative HTML version deleted]]

Add DRM_MODE_ROTATE_ and DRM_MODE_REFLECT_ defines to the UAPI as a convenience. Ideally the DRM_ROTATE_ and DRM_REFLECT_ property ids are looked up through the atomic API, but realizing that userspace is likely to take shortcuts and assume that the enum values are what is sent over the wire. As a result these defines are provided purely as a convenience to userspace applications.

Dear R users, A co-worker and I are writing a function to facilitate graph plotting in R. The function makes use of a lot of lists in its defaults. However, we discovered that R does not necessarily preserve the defaults if we were to input them in the form of list() when initializing the function. For example, if you feed the function codes below into R: myfunction=function( list1=list

if i want to plot the chi-square distribution with a different degree of freedom how can i plot it in the graph?Sometimes i plot the histogram and cut it in a lot of piece.It's distribution like a chi-square.So i want to plot the chi-square with a different degree of freedom to compare it . -- View this message in context:

Hi, How to mark points on x axis of a graph keeping x axis as constant and changing y from y1 to y2 respectively. I want to highlight the area from y1 to y2. Any suggestions Thank you Jeet [[alternative HTML version deleted]]

Dear R-people, I hope asking this is not too cheeky, but I do have a R Problem. I hope that some of you like to play around with R and can help me. Its like this. I have several plant species (A,B,C) and 10 replicates per species. 5 plants per species are damaged, 5 not. I let a caterpillar feed on each plant and measured the growth of the caterpillars on control plants (CR) and on damaged

Hello, I have a graphics-related question: I was wondering if anyone knows of a way to create a bar chart that is colored with a three-part gradient that changes at fixed y-values. Each bar needs to fade green-to-yellow at Y=.10 and from yellow-to-red at Y=.20. Is there an option in a package somewhere that offers an easy way to do this? Attached is a chart I macgyvered together in Excel using a

Hello Imagine I have a vector with ones and zeroes I write it compactly: 1111111100001111111111110000000001111111111100101 I need to get a new vector replacing the "N" ones following the zeroes to new zeroes. For example for N = 3 1111111100001111111111110000000001111111111100101 becomes 1111111100000001111111110000000000001111111100000 I can do it with a for loop but I've read

Hi, all, I would like to know if there is any gui interface out there (academic or commercial) that allows one to edit R-language generated graphs (e.g positioning x axis labels.) It would be nice to have something like the user interface of Igor or Origin. I have already used JGR and R-gui. These are good, but they don't allow one to easily edit graphs. I have also tried

Hi, The standards for audio and video to be used by the Wikimedia projects (like Wikipedia) are Ogg Vorbis and Ogg Theora. The use of Ogg Vorbis files is growing fast. For now the use of video is still very limited. The problem is that an audio and an video file looks the same because of the same file extension. This is very annoying because you do not know what for file it is when you look at

Hi, All, I have a dataset with binary response ( 0 and 1) and some numerical covariates. I know I can use logistic regression to fit the data. But I want to consider more locally. So I am wondering how can I fit the data with 'loess' function in R? And what will be the response: 0/1 or the probability in either group like in logistic regression? Thank you, Cindy [[alternative HTML

Dear All, Does anybody know if there is a functionality in R to break histograms that show a clear bi-modal (or multi-modal) distribution into a series of unimodal histograms that added up result in the original histogram? I was thinking of using QQ-plots (for which tools are available in R), and then observing the number of times the observed quantiles cross the 1:1 line, but this only gives an

R2.7.1, WinXP Hi, I have a polygon inside a circle as follows: radius <- 3 x <- seq(-radius,radius,length=2000) y <- sqrt(radius^2-x^2) xx <- c(x,-x) yy <- c(y,-y) plot(xx,yy, xlim=c(-radius,radius),ylim=c(-radius,radius), type="l", ylab="", xlab="", axes=F) radius <- 2.7 x1 <- seq(-radius,radius,length=2000) y1 <- sqrt(radius^2-x1^2)