similar to: smoothScatter() and the KernSmooth package

Hello, I have found that in smoothScatter it is not possible to reverse the axes plotted (R version 2.9.0) .   It appears that this arises from the hard coding of xlim and ylim in smoothscatter.R in the lines : x <- x[ xlim[1] <= x[,1] & x[,1] <=xlim[2], ]   (line  number 25) and x <- x[ ylim[1] <= x[,2] & x[,2] <= ylim[2], ]  (line number 31) This results in a x

Hi: Is there a way to get smoothScatter to not clip when I increase the xlim and ylim parameters? Consider the following example: set.seed(17) x1<-rnorm(100) x2<-rnorm(100) smoothScatter(x1,x2) #Now if I increase xlim and ylim notice that the plot seems to be clipped at the former xlim, and ylim boundaries: smoothScatter(x1,x2, xlim=c(-5,5), ylim=c(-5,5)) Thanks. Jen sessionInfo() R

Dear all, I am using the smoothScatter function in base R for a plot - Lab.palette.both <- colorRampPalette(c("darkblue","lightblue","red","yellow"), space = "Lab") smoothScatter(X24fresh.sorted[,c(13,10)], colramp = Lab.palette.both) I understand that my yellow colored points represent highest density, red lower, lightblue even lower etc.

Hello everybody, I'm here with a question concerning obtaining a greographical map with a smmothed scatterplot overlaying the intersted regions. My data are a set of opints, represented by long, lat coordinates. As far as the map is concerned, a shp file of Europe without countries borders (only coastal outlines) with the limits at lat 35N-60N long 15W-30E. Until now, I was only able to

On Tue, 18-Dec-2007 at 11:21AM -0500, James W. MacDonald wrote: |> Duncan Murdoch wrote: |> > Yes, I agree. (As an aside, there's actually a capital S in |> > smoothScatter(), and it's a bit of a pain to install, because |> > geneplotter depends on something that depends on DBI, which is not so |> > easily available these days.) |> |> Somehow I always

Hello, I'm having some trouble getting a good result for a smoothScatter plot. I have some data that I want to log-plot, but when I use smoothScatter the result is not correct. The problem seems to be that with the log="x" argument smoothScatter calculates the bins linearly, so the plot will be skewed towards the right. See for example:

Hi, I have been trying to plot density plots using the example on: http://addictedtor.free.fr/graphiques/graphcode.php?graph=139 I used to use this function, but I cannot get any old code or even the example to work. library("geneplotter") require("RColorBrewer") x1 <- matrix(rnorm(1e4), ncol=2) x2 <- matrix(rnorm(1e4, mean=3, sd=1.5), ncol=2) x <-

Epanechnikov kernel works if option canonical=TRUE, however it would be good to know why it does not for for canonical=FALSE (default). Sorry for craetaing maybe useless thread. Best regards, Ondra. [[alternative HTML version deleted]]

The following are now on CRAN: KernSmooth: version 2.2 of the code for Wand & Jones book on kernel smoothing. logspline: spline fits to log denisites, with automatic choice of smoothing. ppr: projection pursuit regression. rpart: recursive partitioning (CART-like) VR: Venables & Ripley libraries 5.3pl021 for 0.62.1 and in the devel section tree: a clone

The following are now on CRAN: KernSmooth: version 2.2 of the code for Wand & Jones book on kernel smoothing. logspline: spline fits to log denisites, with automatic choice of smoothing. ppr: projection pursuit regression. rpart: recursive partitioning (CART-like) VR: Venables & Ripley libraries 5.3pl021 for 0.62.1 and in the devel section tree: a clone

Hi, just a quick question does dpill computes the bandwidth or half-bandwidth? The help says bandwidth, but in the literature there is often confusion between the bandwidth and half-bandwidth. thanks, Giacomo [[alternative HTML version deleted]]

Any advice when to use denstity() and when the KernSmooth package bkde() to smooth a histogram? No specific problem to use either one, but I'm curious why there are two so similar implementations. Thanks! mario -- Ing. Mario Valle Data Analysis and Visualization Group | http://www.cscs.ch/~mvalle Swiss National Supercomputing Centre (CSCS) | Tel: +41 (91) 610.82.60 v.

Dear R users, I am currently using the locpoly function from the KernSmooth package to estimate densities. However, I have some trouble understanding how this estimation technique is implemented in R. My main concern comes from the fact that this function gives negative estimates when the bandwidth is sufficiently large (mainly in the tails of distributions). I have read some articles on this

Hello, I am attempting to use smoothScatter to plot a heatmap of locations of events in an x-y axis. When I plot the heatmap without passing xlim and ylim parameters, it fills the plot area but the perspective is a bit skewed. I would like to standardize these plots to a uniform window size that does not depend on the range of values in the dataframe. However, when I resize the plot using xlim or

According to the CRAN contributed packages page, the license for "KernSmooth" is *not* GPL. It is listed as "License: Unlimited distribution (from Dr Wand)." Are there any restrictions on this of any kind? Is there some written license document similar to the GPL license? The reason I'm asking is that the legal beagles in the company I work for are extremely paranoid about

Hi, I have two separate questions relating to the KernSmooth package. I am using the dpik function from the KernSmooth package and receive the error Warning message: In kappam * Gcounts : longer object length is not a multiple of shorter object length I saw an earlier post , but the issue was using the bkde fxn and the person appeared to be using too small of a bandwidth.

Hi all, I'm not sure who to ask this, so I'm posting this here. I just ran: require(KernSmooth) And got (I bolded the text): Loading required package: KernSmooth KernSmooth 2.23 loaded *Copyright M. P. Wand 1997-2009* Warning message: package 'KernSmooth' was built under R version 2.12.1 What does that mean? Thanks, Tal ----------------Contact

Hello, I have a few questions, regarding the smoothScatter function. I have a scatter plot with more than 500,000 data points for two samples. So, I am wanting to display the density in colors to convince people that my good correlation coefficient is not due to an "influential point effect" and plus, I also want to make my scatter plot look pretty. Anyway ... I have been able to

I just upgraded to R 2.7.2 (from 2.7.1) this morning (Ubuntu amd64 platform). Shortly afterwards, I ran into a problem loading the odesolve library, it could not find libRblas.so. I was able to fix this by rebuilding odesolve. Now, KernSmooth gives me the same problem... R> library(KernSmooth) Error in dyn.load(file, DLLpath = DLLpath, ...) : unable to load shared library

Hello, I'm using R 1.40 on MacOS X X.1.2 (installed via the fink package manager). To upgrade my installed packages, I tried to use update.packages() today. All went well for most packages, with the exception of KernSmooth and cluster. In both cases, libraries were not found although I think they are present. Here's what happened: ---------------------------------- >