search for: plogsplin

Dear R-list, I have made a simple kernel density estimation by x <- c(2,1,3,2,3,0,4,5,10,11,12,11,10) kde <- density(x,n=100) Now I would like to know the estimated probability that a new observation falls into the interval 0<x<3. How can I integrate over the corresponding interval? In several R-packages for kernel density estimation I did not found a corresponding function. I

I'm implementing a new testing procedure proposed by Chen, Ying, Zhang and Zhao (Biometrika, 2008) that employs a reference distribution obtained by a resampling method. For the moment I'm using logspline to estimate the reference density and then computing the p-value using plogspline. I would be interested in hearing about other suggestions from anyone who has looked at similar situations. url: www.econ.uiuc.edu/~roger Roger Koenker email rkoenker at uiuc.edu Department of Economics vox: 217-333-4558 University of Illinois f...

Hi there, I have two series of data. plotting the density function of both gives me an idea about the difference of the data. But I would like to quantify the difference I see. a <- rnorm(100) b <- rnorm(100) da <- density(a) db <- density(b) The problem is that da$x and db$x are different and so I have difficulties to compare them... Is there any way to force the density