similar to: Fetching datapoints from a Time Series

Hi there. I have the following graph: http://www.nabble.com/file/p10928148/map.jpg However, some datapoints occur at the same place as other datapoints and are so layered on top of each other. I would like to know if there is any possible way in which I could view those datapoints that are layered on top of each other ...maybe by rotating using latitude to show the datapoints underneath (but

Dear Ms and Mr R, I am seeking a visually appealing presentation of 3 variables (~30 datapoints) that are correlated and that should to into the same direction. The objective is to show that they do go in the same direction and what differences there might be while also giving an idea of the values of the variables. I had done this with simple bargraphs for 6 datapoints in the past, but for

It is known that function bkde2D (package "KernSmooth") returns a matrix of density estimates over the mesh induced by x1 and x2. In Details it is written that "... heights of the kernel, scaled by the bandwidths, at each datapoint are summed. This sum, after a normalization, is the corresponding fhat value in the output". There are several questions: 1) How to calculate

Hi, I managed to make R core dump (linux and Mac OSX versions), but I think I've figured out why. First, here's the message I get on core dump (on linux - no message on Mac): R: ../inst/include/tnt/fmat.h:529: TNT::Vector<T> TNT::matmult(const TNT::Fortran_Matrix<T>&, const TNT::Vector<T>&) [with T = double]: Assertion `A.num_cols() == x.dim()'

Thanks, Martin. Based on my previous post, I thought of a more general formulation of my question that I think would be helpful to ask here. What's the best way to build an R object that links multiple datapoints about different people? I mean, I happen to have datasets that have individual gene expression data tied to individual patient characteristics (how long they survived, age, gender,

Hello!!! I'm just a beginner of R. I work with locfit to get the density from an numeric vector. It looks good when I plot the graph, but I need the output data of locfit. For example I need somthing like that (only integer values for the input): numeric vector (input of locfit) density (output of locfit) 1 0.05.... 2 0.04.. 3 0.01 ... Thank you for your help and your time.

Hi, In the getGraphicsEvent function the (x,y) co-ordinates returned from the mouse move are in relation to where the mouse is located within the device window (i.e. the lower left corner of the window is '(0,0)', the upper right is '(1,1)'). Is there a way of returning the (x,y) co-ordinates of data points plotted where instead of x and y being the actual data points they are

Hello!! At first thank you all for your suggestions and your help. But I would like to get another group of datas from the density estimation. I don't know if these information are provided by locfit or I should use an other function like plot(). Description: Each number between 1 and 100 (only integer) for example should have only one density value. But I also would like to have the density

Andrew Purtell wrote: > I routinely fetch the latest LLVM and LLVM-GCC4 and recompile, perhaps every few days or so. I've not had success in some cases building LLVM-GCC4 on a Gentoo Linux host, for perhaps the last week or so. My system compiler is GCC 4.1.1. > > > cc1: /usr/src/llvm/llvm/include/llvm/Target/TargetInstrInfo.h:151:const llvm::TargetInstrDescriptor&

Dear All: We have been experiencing networking issues so I don't know if this got through; I can't see it in the archive. My sincere apologies if this appears twice. I may have found an unusual bug and am posting here to see if anyone can reproduce it on their system. First of all, sessionInfo(): > sessionInfo() R version 2.7.1 (2008-06-23) i386-apple-darwin8.10.1 locale:

I routinely fetch the latest LLVM and LLVM-GCC4 and recompile, perhaps every few days or so. I've not had success in some cases building LLVM-GCC4 on a Gentoo Linux host, for perhaps the last week or so. My system compiler is GCC 4.1.1. >>> cc1: /usr/src/llvm/llvm/include/llvm/Target/TargetInstrInfo.h:151:const llvm::TargetInstrDescriptor&

We have a large install of 360's running rev 4.1 with zero problems. I did another, smaller install couple weeks ago with 40 360's running rev 5.3. In both cases, the install was identical, same Asterisk version, same dialplan, everything the same except the differences were: 1. Different firmware rev 2. Different physical LAN Guess what? On the smaller install, lockups and reboots.

Dear R community, I am creating large graphs with hundreds of thousands of datapoints. My usual way for output was pdf, but now I am getting file sizes of >30Mb that do not open well (or at all) in Adobe. Is there a way to reduce the resolution or get rid of overlaying datapoints? Any other idea is also warmly welcome! Thank you and wishing you a good day! Georg. **********************

Hi all, here is my situation In my experiment, I expose 10 subjects to 24 different conditions of stimuli. Each condition is exposed to the same subject 3x. This would make each subject have 24x3=72 data points. All the subjects combined would have 72x10=720 data points with each condition having 30 datapoints. To find the grand average of each condition, I find the average of all the

Hello, I am trying to plot age distribution data for a certain condition that runs in families. Below is a simplified view of the dataset, i.e. in this case there are four families, each line corresponding to one individual with age at diagnosis and sex. > famdata family age sex 1 fam1 2.1 f 2 fam1 2.3 f 3 fam1 1.0 m 4 fam2 7.3 f 5 fam2 4.1 f 6 fam2 1.2 f 7

Hello, I'm currently using a simple plot to visualize some mean values. I'm having ~200 datapoints on the x-axis, each has 10 records. I'm currently plotting only the mean value of each of the datapoints. What I need is a way to visualize the quartiles/error/whatever of these points. I thought about boxplots, but I have to many points on the xaxis - it would be impossible to see

I am trying to do something in R and would appreciate a push into the right direction. I hope some of you experts can help. I have two distributions obtrained from 10000 datapoints each (about 10000 datapoints each, non-normal with multi-model shape (when eye-balling densities) but other then that I know little about its distribution). When plotting the two distributions together I can see that

I have a table that looks like this: measurement?? ?date??? door ?? color 0.93529385?? ?513?? ?open?? ?red 0.97419293?? ?420??? open ?? red 0.962053514?? ?513?? ?closed?? ?red 0.963909937?? ?1230?? ?open?? ?blue 0.97652034?? ?1230?? ?open?? ?green 0.989310795?? ?1230?? ?closed?? ?blue 0.9941022?? ?917?? ?closed?? ?yellow I would like to create a table that has: Open measurement, Closed

Hi- I am trying to find a way to diffuse GIS data on a European map. I have a dataset consisting of particular locations scattered across Europe, along with magnitude and value information. I can plot these as discrete points with something like the following: "geocode" is a dataframe with four columns: LAT; LONG; MAGNITUDE;VALUE. library(maps) library(mapdata)

Hello, I have simulation results in the form of Time V I 0.000000000000e+000 7.218354344368e-001 5.224478627497e-006 1.000000000000e-009 7.218354344368e-001 5.224477718002e-006 2.000000000000e-009 7.218354344368e-001 5.224477718002e-006 4.000108361244e-009 7.218354344368e-001 5.224478627497e-006 8.000325083733e-009