similar to: Binning groups

Dear all, I have a binned data that looks like this: > dat (-1,9] (9,19] (19,29] (29,39] (39,49] (49,59] (59,69] (69,79] 10063374 79 16 4 3 4 4 3 (79,89] (89,99] 6 2 I tried to plot a histogram overlayed with curve. With the following snippet: library(lattice) pdf("myfile.pdf") hist(dat)

Hi, I'm trying to setup some complicated binning with statistics and could use a little help. I've found the bin2 function from the ash package, but it doesn't do everything I need. My intention is to copy some of their code and then modify as needed. I have a vector of two columns: head(data) r1 r2 [1,] 0.03516559 0.03102128 [2,] 0.02162539 0.14847034

Full_Name: Gerald Guglielmo Version: 2.8.1 (2008-12-22) OS: OSX Leopard Submission from: (NULL) (131.225.103.35) When I attempt to use the hist() function to bin integers the behavior seems very odd as the bin boundary seems inconsistent across the various bins. For some bins the upper boundary includes the next integer value, while in others it does not. If I add 0.1 to every value, then the

Good day, I have been unable to solve this issue. Do you get grainy fonts when running the test case plot(1:10, main = "abcedfghijklmnopqrstuvwxyz", cex.main = 4, cex.lab = 4, cex.axis = 4) What version of libcairo is on your system ? -------------------------------------- Dario Strbenac PhD Student University of Sydney Camperdown NSW 2050 Australia

I would like to 'bin' a vector of of values (>100000 values) in much the same way as 'hist' does for plotting, but I just want a result with the bins and the frequencies. Is there a 'quick and dirty' (built-in) way to do this, or do I need to write some code? Many thanks, Robert Terwilliger

Hello, I am having problem with binning the data. I have a 50X3 matrix and I binned the data for all the 3 columns. Using table command I got the total no. of elements in a particular bin. Could you please tell me how to see that what all elements are there in a particular bin and then create a different matrix for each bin? Thanks. Regards, Sumit [[alternative HTML version deleted]]

Hi, I'm looking for a super-duper fast mean/sum binning implementation available in R, and before implementing z = binnedMeans(x y) in native code myself, does any one know of an existing function/package for this? I'm sure it already exists. So, given data (x,y) and B bins bx[1] < bx[2] < ... < bx[B] < bx[B+1], I'd like to calculate the binned means (or sums)

Hello, I was wondering wether there's a function in R that takes two vectors (of same length) as input and computes mean values for bins (intervals) or even a sliding window over these vectros. I've several x/y data set (input/response) that I'd like plot together. Say the x-data for one data set goes from -5 to 14 with 12,000 values, then I'd like to bin the x-vector in steps of

Newbie here. Many apologies in advance for using the incorrect lingo. I'm new to statistics and VERY new to R. I have a "nx2" matrix , I want to sort the values based on the average of 2 columns and put k lowest (or highest) values in bin1, second k high/low values in bin2, and so on (bins would be of the same dimensions). I should also know what the first index (or position) of

Hi, Short Version: Is there a function to re-bin a histogram to new, broader bins? Long version: I'm trying to create a histogram, however my input-data is itself in the form of a fine-grained histogram, i.e. numbers of counts in regular one-second bins. I want to produce a histogram of, say, 10-minute bins (though possibly irregular bins also). I suppose I could re-create a data set as

The standard chisq.test() and fisher.test() functions, when applied to two distributions (to determine whether the same underlying distribution applies to both) requires one to pre-bin the distributions. Is there a library function (either built-in or in a package) that acts more like the ks.test() function, in that one can simply pass the two distributions and have it do the necessary binning as

Hi all, I have a situation where I have 16 bins. I generate a random number and then want to know which bin number the random number falls in. Right now, I am using a serious of 16 if() else {} statements which get very complicated with the embedded curly braces. Is there a more efficient (i.e., easier) way to go about this? boundaries<-(0:16)/16 rand<-runif(1) Which bin number (1:16)

Dear List: I have a dataset with over 5000 records and I would like to put the Count in bins based on the ForkLength. e.g. Forklength Count 32-34 ? 35-37 ? 38-40 ? and so on... and lastly I would like to plot (scatterplot) including the SampleDate along the X axis and ForkLength along the Y axis. I recently saw an example similar to

Hello, Suppose I have the dataset shown below. The amount of observations is too massive to get a nice geom_point and smoother on top. What I would like to do is to bin the data first. The data is indexed by Time (minutes from 1 to 120 i.e. two hours of System benchmarking). Option 1) group the data by Time i.e. minute 1, minute 2, etc and within each group create bins of N consecutive

First, thanks to everyone who helped me get to grips with R in (x)emacs (I get confused easily). Special thanks to Stephen Eglen for continued support. My question is about non-linear binning, or density functions over distributions governed by a power law ... y ~ mu*x**lambda # In one of its forms # (can't find Pareto in the online help) Looking at the following

How can perform logarithmic binning in the scatterplot? I could only take the log of the variables and plot them, but I am sure that is not the way. I have a very huge data, and would want to plot those high density scatterplots and code then with different colors for the bins/density. -- View this message in context:

Thanks for letting us try this. On my 1.5M DSL line in Pasadena CA USA, I get the 128k stream real good, output to Alesis M1 Active monitors. The fidelity is fine, as far as what I think the content probably sounds like. The 64K stream comes in fine as to throughput but sounds quite grainy, smeared and flangy high freqs. Well, you asked for reports. Keep up the good work. --- >8 ----

Dear helpers, I've looked in the help files (maybe not very thoroughly but I looked) and I couldn't find a straightforward way to permanently set the working directory (where I save and read files). Each time I startup R the working dir is automatically "C:/R/bin" [using:getwd()], and I know I can change it using setwd [for example setwd("C:/R/DATA"), but it's only

Hello I have a large series of data value -- effectivly say the point across the x-axis where a pitch crosses home plate. What I want to do is find the % of ground balls at various distances across home plate. I therefore need to 'bin' the two data sets I have - plate location for ground balls and plate location for all other outcomes. Question is how can I set up a series of bins

I am trying to produce frequencies in defined intervals however I can't seem to figure out how to get R to bin my data the way I want it to. I have several thousand lengths of fish that I want to be binned as follows: Ex. Length Bin 209 200 219 210 431 430 727 720 That is, bins with any length equal to or greater than the lower