similar to: estimating quantiles from binned data

Given a set of data: > names(data) [1] "city" "house" "visit" "value" I am looking for a way to compute the variance components of the nested model (ie, visit 1 at house 2 at city 3 isn't related to visit 1 and house 2 at city 4), but different houses in the same city may be related, and different visits to the same house are probably

I am trying to use rsync for making snapshots, sharing hardlinks at the destination using the --link-dest option. In conjunction with this, I would like for --dry-run to report some reliable-ish number for how much space it is going to consume at the destination so that I can arrange to free such space prior the launching rsync "for effect". Right now, that isn't working: #

Hi all I hope you might help me with some aspects of producing a graph in lattice. There are three things I have struggling with and that is: 1. to separate the horizontal box rows from each other; 2. to change the colour of the horizontal and vertical strips to white; and 3. to place the axes labels on the left y axes and on the bottom x axes. I would really appreciate some help. I have put the

Hi all I was wondering if it is possible to get rid of the horizontal strips and produce each barchart with a left y axes and lower x axes only. Also can you specify an exact size of graph ie 88mm wide with a font size of 'x'. library(lattice) library(latticeExtra) n=as.factor(c(1:5,1:5))

How to use ggplot to do the binned quantile plots(one type of scatter plot)? Hi all, I have done scatter plot: plot(x, y). Now I wanted to do binned quantile plots... can ggplot2 help me? For example, we bin x data into 10 bins. For each bin, we draw the 10 deciles of the corresponding y data in that bin as points/dots. And then accross all bins, we would like to connect the corresponding

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 R-Users, I read some texts related to KS-tests. Most of those authors stated, that KS-Tests are not suitable for binned data, but some of them refer to 'other' authors who are claiming that KS-Tests are okay for binned data. I searched for sources and can't find examples which approve that it is okay to use KS-Tests for binned data - do you have any links to articles or

Dear All, I am researching financial market microstructure and have approx 4 x 10^7 multivariate 2D data samples which I have counted into a 250 x 390 bin matrix (frequency counted 2D histogram) in order to more efficiently manage the volume of data. I now wish to construct a smooth kernel density estimate (Gaussian kernel function) using this binned data. Does anyone in the R community know

Hello I need to fit a distribution to a histogram data set. I have read Ricci's guide to distribution fitting, and am ready to begin experimenting with the techniques it mentions, but I am uncertain how to get my data in the format he uses. My problem is that my data is binned. So for example my data is in the following format #lb ub count 0 1 4 1 2 7 2 3 2

Hi, I'm trying to create a plot showing the density distribution of some shipping data. I like the look of violin plots, but my data is not continuous but rather binned and I want to make sure its binned nature (not smooth) is apparent in the final plot. So for example, I have the number of individuals per vessel, but rather than having the actual number of individuals I have data in the

Hi, I am attempting to tabulate binned data. The '1' represents the appearance of the focal mouse pup, and '2' represents the disappearance of the focal mouse pup. The code written below is intended to calculate the total time spent appeared out of 3600s. For Sample 1, both the hand calculation and R code yield the same result, 50. A problem seems to occur when '1' is the

Hi, I'm a newbie in using R and I would like to have a few clues as to how I could compute and plot a distribution of daily rainfall intensity in different categories. I have daily values (mm/day) for several years and I need to show the frequency of 0-1, 1-2.5, 2.5-5, 5-10, 10-20, 20+ mm/day. Can this be done easily? Thanks, Etienne

I have a table that looks like this: structure(list(speed = c(3,9,14,8,7,6), result = c(0.697, 0.011, 0.015, 0.012, 0.018, 0.019), house = c(1, 1, 1, 1, 1, 1), date = c(719, 1027, 1027, 1027, 1030, 1030), id = c("1000", "10000", "10001", "10002", "10003", "10004")), .Names = c("speed", "result",

Dear all, I would like to know how can I create a binned column in a data.frame. The output that I would like is something like this: Start Binned_Start 1 0-5 2 0-5 6 5-10 8 5-10 13 10-15 ... Best regards João Fadista Ph.d. student UNIVERSITY OF AARHUS Faculty of Agricultural Sciences Dept. of Genetics and Biotechnology Blichers

Hi, Standard correlations (Pearson's, Spearman's, Kendall's Tau) do not accurately reflect how closely the model (GAM) fits the data. I was told that the accuracy of the correlation can be improved using a root mean square deviation (RMSD) calculation on binned data. For example, let 'o' be the real, observed data and 'm' be the model data. I believe I can calculate

I have a scatter plot with 10000 points.? I would like to add a line that bins every 50 points and connects the average of each bin.? I'm looking for something similar to line type "m" in Stata. With this dataset of 10000 points, I would also like to bin the data and make boxplots at certain intervals, so that I have a set of boxplots to represent each bin.? I would also like the

Dear list, I have a vector (array, table row, whatever is best) of frequency values for categories (or bins), and I need to find the median category. Trivial to do by hand, but I was wondering if there is a means to do it in R in an elegant way. The obvious medioan(vector) returns the median frequency for the binns, and that is not what I want. i.e,: freq cat1 1 cat2 10

Dear all, I need to build a PBX based on Asterisk for a call center. I have worked with raw Asterisk but it's hard to work for big implementations think. Also I have worked with Trixbox CE for a small bussines and it was prette good, but I have not have many features like ACD. I know there is another version called Trixbox PRO -specially Call Center edition- that's not free but has got

Full_Name: Anthony Gichangi Version: 1.90 OS: Windows XP Pro Submission from: (NULL) (130.225.131.206) The function rlnorm generates negative values for lognormal distribution. x- rlnorm(1000, meanlog = 0.6931472, sdlog = 1) Regards Anthony

Dear List, I have read that a lognormal mixture model having a pdf of the form f(x)=w1*f1(x)+(1-w1)*f2(x) fits most data sets quite well, where f1 and f2 are lognormal distributions. Any pointers on how to create a function that would produce the 5 parameters of f(x) would be greatly appreciated. > version _ platform i386-pc-mingw32 arch i386 os