similar to: compressing/reducing data for plot

Dear All I hope that someone can help. I am working with sp pakage and akima library("akima") library(sp) imagine lots of different dataframes, of row = 100 columns = 3 of x and y coordinates with z values I will call these data frames for the sake of this example akima akima<-as.list(1:100) producing 100 dataframes dataframes of the form akima[[i]] I then wish to interp this

With Dotplot, I'm trying to make a figure that will ultimately have the same x-axis (which will be my response variable and the error bars), but the y-axis will consist of a different label for every point. Here's my code: Dotplot(fTaxonGrouped ~ Cbind(normSlope,normLwr,normUpr)|fGroup, groups=fEpoch, pch=c(17,15,19), col=c(3:1), scales = list( y = list(relation =

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

Dear All I am reposting because I my problem is real issue and I have been working on this. I know this might be simple to those who know it ! Anyway I need help ! Let me clear my point. I have huge number of datapoints plotted using either base plot function or xyplot in lattice (I have preference to use lattice). name xvar p 1 M1 1 0.107983837 2 M2 11

Hello All, this is my first post so I'll try to be as verbose as possible. We have a PXE deployment server serving mostly fujitsu RX300 rack mount servers with Intel 82575EB Gigabit Ethernet Controllers onboard. I recently upgraded from version 4.07 to version 6.02 and, without making any edits to my default menu, immediately noticed a regression. I use vesamenu.c32 to present a menu to the

Hi I have to time series with a different time base. The first has only sporadic datapoints: 2011-02-01 15.29130 2011-02-08 17.60278 2011-02-15 17.99737 2011-02-22 25.43690 The other has a daily datapoint: 2011-02-01 342.34 2011-02-02 68.45 2011-02-03 130.47 2011-02-04 129.86 2011-02-05 81.98 2011-02-06 77.30 2011-02-07 81.38 2011-02-08 139.95 2011-02-09 124.40 ...etc. In Excel, it is fairly

Dear List, I am new to lattice plots, and am having problems with getting my plot to do what I want. Specifically: 1. I would like the legend to have the same symbols as the plot. I tried simpleKey but can't seem to get it to work with autoKey. Right now my plot has dots (pch=19) and my legend shows circles. 2. I have nine groups but xyplot seems to only be using seven colors, so two

Greetings, I''ve got a rails app which is basically an admin interface to a xml dataset. Currently I''ve got rails rigged to call a function to spit the entire dataset to file with every change. This would actually be ok, its fairly infrequently updated, but when the dataset grows large the user sits there waiting for it to dump with no feedback as to whats going on. Oh yes,

Hi, I drew a plot with R of my data and now I would like to display the median values of each group above the respective datapoint in the plot. I already search for ages, but maybe I am just blind. I am sure that this has to be an option somewhere... I appreciate any kind of input! Best, Christian

Hello everyone, i am currently creating a barplot. This barplot takes a vector of ~200 datapoints. Each datapoint represents one bar. http://img96.imageshack.us/i/human1w.png/ (Ok as you see, it is not only one barplot, but a series of barplots). Now, these barplots represent a human chromosome. This means they are ordered. For instance bar number 50, means position 50 in the human chromosome.

Dear Group, I have the following data matrix which is a timeseries. > dput(tData) structure(list(A = c(0.2, 0.13, 0.05, 0.1, 0.02, 0.18, 0.09, 0.06, 0.13), B = c(0.15, 0.06, 0.09, 0.02, 0.03, 0.12, 0.01, 0.15, 0.06), C = c(-0.1, 0, -0.07, -0.06, -0.05, -0.05, -0.06, -0.08, -0.07), D = c(-0.15, -0.05, -0.1, -0.03, -0.13, -0.04, -0.1, -0.04, -0.15), E = c(-0.17, -0.16, -0.08, -0.07, -0.09,

On 6 July 2018 at 12:31, Enrico Schumann wrote: | Just as one more datapoint: I cannot reproduce the segfault, with | R 3.5.1 on (L)Ubuntu 18.04. (I use the Ubuntu package, i.e. I did not | build from source.) I have been a little too busy and have not yet upgraded to 18.04 so I can't attempt to replicate -- but it _looks_ just like a garden variety binary mismatch. We _know_ R 3.5.*

I have been asked to forward this. Please reply directly or include the people who have been CC-ed in this e-mail. Thank you. > forwarded message from "Timothy Waters" <timothy.waters at plant-sciences.oxford.ac.uk> ----- > > Consider the following problem. You have a dataset with approx 190 > datapoints. Each datapoint has between 7 and 16 dimensions known: most

Gene, Ady thanks for your suggestions. >> What if you dropped the timeout to 0.8-2.0 seconds or even 0.2 seconds? I tried setting the delay to 2 seconds and 0.2 with no change in behavior. >> First, please be sure you are using all C32 modules from the exact same Syslinux version, including ldlinux.c32 and all lib*.c32 library modules, all located somewhere under the

Hi, I have a question about predicting new values from a fitted model in R. For example, if i fit a linear model fit<-lm(y~x) predict(fit) will give the fitted values for each x. I am wondering if there is a way to do some prediction of the fitted for some new values of x that are not in the data points? for example, x=0.5 is not in the original data (not a datapoint), is there a way to

Hello, I have a large data frame (1006222 rows), which I subject to a crude clustering attempt that results in a vector stating whether the datapoint represented by a row belongs to a cluster or not. Conceptually this looks something like this: Value Cluster? 0.01 FALSE 0.03 TRUE 0.04 TRUE 0.05 TRUE 0.07 FALSE ... What I'm looking for is an efficient strategy to extract all

Hello, I once used the metawin software to perform a meta-analysis (see metawinsoft, Rosenberg et al.) and produced normal qqplot to test for a potential bias in the dataset. I now want to re-use the same dataset with the package metafor by W. Viechtbauer (great package btw). I run the qqnorm.rma.uni function. I use standardized effect sizes as in metawin. QQplot generated with metafor differs

I''m just getting started with GD2 and have successfully made a few dynamic PNGs. I need to make some fairly detailed line graphs on the fly and I know that GD2 is capable of what I want but I strongly suspect I''m reinventing the wheel badly. Are there gems or other projects that help creating complex charts? I''ve used GDChart in the distant past but I

On Tue, Sep 06, 2005 at 09:56:06PM -0500, Jay Krivanek wrote: > Yea, don't get me wrong, ogg is definitely an awesome format but aacplus v2 > is currently the leader in high fidelity quality at low bitrates. 24kbps > aacplus even kicks ass in my view. Is that 24kbps AACPLUS a full 44.1kHz stereo signal with frequencies preserved up to at least 15kHz? (Just curious, not

Dear R-forum, I am looking for a good resource/help on working with POSIXct values and controlling the pretty x-axis labels and tick marks for a data VS time plots. Specifically, I wish to do programming logic which creates different vertical ablines calculations based on the range of times which i am working on. The default plot results are adequate, but I would love to make explicit calls on