similar to: Kernel Density estimation at specific points

Dear all, I am a little bit puzzled by the way round() works. Consider the following code >a<-123456.3678 > round(a,digits=10) [1] 123456.4 I would expect the outcome to be something like 123456.3678 or 123456.368, instead the computer gives me 123456.4 no matter how large the digits are. Can anybody help me understand what I'm missing here? Thanks again for your help. Robert

Hello, my name is Carsten. This ist my first post to R-help mailing list. I estimate densities with the function "density" out of the package "stats". A simplified example: #generation of test data n=10 z = rnorm(n) #density estimation f=density(z,kernel="epanechnikov",n=n) #evaluation print(f$y[5]) Here I can only evaluate the estimation at given

Hi all, I'm trying to load the quantreg package but keep running into problems no matter which method I have tried. Does anybody know what this error (below) means in plain language and what I might do to get this installed. I have not had problems downloading/installing/running packages in the past. thanks in advance, derek Begin R output: trying URL

Hi, I am starting to use Mapstraction with the openlayers provider, and I am not sure how to retrieve the current center of a map in a cross-provider way. i.e. currently when calling map.getCenter(), the result returned is the openlayers internal one, not the long/lat used when calling setCenter(). Is that the expected behaviour? Regards, Philippe -------------- next part -------------- An

There are a bunch of us working on LLVM in Austin. So we're organizing a LLVM Austin Social in September. The social will be on Wednesday, September 12 from 5 pm at the BB Rovers Cafe and Pub. It'll be great to meet up with folks in Austin who are also interested in LLVM. Please reply and let me know if you plan on attending so that I can get a count. BB Rovers is on Jollyville road

Dear group, Thank u so much 4 ur help. I've tried the link, http://finzi.psych.upenn.edu/R/library/quantreg/html/akj.html for adaptive kernel density estimation. But since I'm an R beginer and the topic of adaptive estimation is new for me, i still can't figure out some of the arguments of akj(x, z =, p =, h = -1, alpha = 0.5, kappa = 0.9, iker1 = 0) I've a vector of 1000 values

Dear R users, I have a problem computing time differences using R. I have a date that are given using the following format: 20080620.00, where the 4 first digits represent the year, the next 2 ones the month and the last 2 ones the day. I would need to compute time differences between two vectors of this given format. I tried around trying to change this format into any type of time serie

Dear R contributors, I recently dowloaded the R-1.3.1 on my SGi Origin 200 run by Irix6.5. In order to instal it, I launched the command shown below: env MAKE=gmake ./configure The output was as follow:: R is now configured for mips-sgi-irix6.5 Source directory: . Installation directory: /usr/local C compiler: cc -OPT:IEEE_NaN_inf=ON -g C++ compiler:

Hi, I'm wondering if it is possible to install a package for R 2.0 on R 1.9.1 on Mac OS X? I'm getting this error which seems to be known issue: library("quantreg") Error in firstlib(which.lib.loc, package) : couldn't find function "lazyLoad" In addition: Warning message: package quantreg was built under R version 2.0.1 Error in

Hi! I have two dimensional dataset which has and I need to decide if a point lies in some "confidence level". If a point has low confidence/density it can be anomaly which I need to find. For example: #load library library(sm) #get some data x.locs = c(74, 74.5, 75, 77,74.5) y.locs = c(64, 63.5, 63, 61,61.5) points = cbind(x.locs, y.locs) #plot it plot(points) #get points density

Hi All: I tried to download and install "quantreg" (a package for doing quantile regression) from CRAN. When I ran install.packages ("quantreg") within an R session, I got the following error message: <----Beginning of error message ---> * Installing *source* package 'quantreg' ... ** libs g77 -mieee-fp -fPIC -O2 -g -pipe -march=i386 -mcpu=i686 -c akj.f

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

hello, i am using the hist function with classified values. The class breaks are >1, so histogram$density is != 1. How to plot the histogram with freq=FALSE and the real class density values. I used: > h2 = hist(value, breaks = breaks_vector) > h2$density = round(h2$counts/sum(h2$counts), 2) > h2$intensities = h2$density > plot(h2, freq=F) but this isn't the best way, i

Hello, To indicate probability densities instead of counts on a histogram, I specify freq = FALSE. However, I expect that summing all top y coordinates over all the intervals of the histogram will provide 1. 1) v <- c(0.2885, 0.2988, 0.3139, 0.2615, 0.3179, 0.3163, 0.2583, 0.3052, 0.2527, 0.3147, 0.3235, 0.2408, 0.2480, 0.3108, 0.3577, 0.2829, 0.2694, 0.3275, 0.3314, 0.2639, 0.3076,

Hi List, I have a raster and a polygon with attribute ID and Class. I want to have the fraction of each class present in each pixel of raster. I have use the raster::extract to get the value and weights as below. ex<-extract(raster,polygon,weighted=TRUE) this gives me [[1]] value weight 13943 0.24 13958 0.02 13959 0.84 13960 0.19 13987 0.03 13988 0.31 13990 0.30 [[2]]

Does any have installation instructions for this? When I run install.packages('quantreg') I get: gcc -std=gnu99 -shared -o quantreg.so akj.o boot.o brute.o chlfct.o cholesky.o combos.o crq.o crqfnb.o dsel05.o etime.o extract.o idmin.o iswap.o kuantile.o mcmb.o penalty.o powell.o rls.o rq0.o rq1.o rqbr.o rqfn.o rqfnb.o rqfnc.o sparskit2.o srqfn.o srqfnc.o srtpai.o -llapack -lblas

We probably should not spam the list... but I am in :) Anshu, maybe we can reply directly to you, and at the end you can simply announce the head count? Sergei -- Qualcomm Innovation Center, Inc. is a member of Code Aurora Forum. > -----Original Message----- > From: llvmdev-bounces at cs.uiuc.edu [mailto:llvmdev-bounces at cs.uiuc.edu] > On Behalf Of Anshuman Dasgupta > Sent:

The new package "benchden" 1.0.0 implements 28 benchmark densities for nonparametric density estimation that were introduced by A. Berlinet and L. Devroye ("A Comparison of Kernel Density Estimates", Pub. Inst. Stat. Univ. Paris, XXXVIII, fasc. 3, 1994, 3-59, http://cg.scs.carleton.ca/~luc/devs.html ). This collection includes a variety of densities with different degrees of

The new package "benchden" 1.0.0 implements 28 benchmark densities for nonparametric density estimation that were introduced by A. Berlinet and L. Devroye ("A Comparison of Kernel Density Estimates", Pub. Inst. Stat. Univ. Paris, XXXVIII, fasc. 3, 1994, 3-59, http://cg.scs.carleton.ca/~luc/devs.html ). This collection includes a variety of densities with different degrees of

Dear List, I have been trying to use library sm to do density estimation on a 3D dataset. I am using the current MacOS X binary of sm from CRAN. If I do this on a 2D dataset, sm.density returns a list including the component "estimate" which contains the density estimate over a uniform grid. When doing this with 3D data, although I get a nice plot (even when I don't ask for one),