similar to: ggplot2 month and year boxplot x axis order problem

Hi: Can't find?a way to convert?from shortDate to LongDate format. I?got: 3/10/10 that I want to convert to March 10, 2010. I am using: \documentclass[11pt]{article} \usepackage{longtable,verbatim} \usepackage{ctable} \usepackage{datetime} \title{my title} \begin{document} ? % Convert date \mmmmddyyyydate\3/10/10 end{document}? My report is changing every two weeks so I?will eventually use

Hi: Can't find?a way to convert?from shortDate to LongDate format. I?got: 3/10/10 that I want to convert to March 10, 2010. I am using: \documentclass[11pt]{article} \usepackage{longtable,verbatim} \usepackage{ctable} \usepackage{datetime} \title{my title} \begin{document} ? % Convert date \mmmmddyyyydate\3/10/10 end{document}? My report is changing every two weeks so I?will eventually use

R-Help Please disregard as I figure something out, unless there is a more elegant way ... myData.sum <- aggregate(x = myData[c("s72","s79","s82","s83","s116","s119")], FUN = sum, by = list(Group.date = myData$shortdate)) > head(myData.sum) Group.date s72 s79 s82 s83 s116 s119 1

R-Help I created a "shortdate" for the purpose of aggregating each var (S72 .S119) by daily sum , but not sure how to handle using a POSIXlt object. > myData$shortdate <- strftime(myData$time, format="%Y/%m/%d") > head(myData) time s72 s79 s82 s83 s116 s119 shortdate 1 2016-10-03 00:00:00 0 0 1 0 0 0 2016/10/03 2 2016-10-03 01:00:00

Hi Samba users, We would like to use samba for re-exporting our other distributed file system (BeeGFS). However, we found that the meta data operations are very slow (dir stat, removal etc.). On SMB client the performance is more than 30x slow than on the SMB server. We would expect some slowness but this is too big a drop. This is the result on CIFS client $ sudo mdtest -b 10 -I 10 -L -z 2

Dear all, I have the following output generated by linear regression. Since there is only one regression intercept and one slope for one set of data, what is the meaning of std. error for intercept and that of slope? Thanks in advance. Sincerely, Minghua > data(thuesen) > attach(thuesen) > lm(short.velocity~blood.glucose) Call: lm(formula = short.velocity ~ blood.glucose)

Hello all, I have a simple function which calculates summary statistics of a dataset in terms of a factor (say area). > x = data.frame(Area = c(rep("cleanup", 5), rep("ref", 5)), TcCB = c(rnorm(5)+2, rnorm(5)));x Area TcCB 1 cleanup 2.5829747 2 cleanup 2.6796868 3 cleanup 2.5437094 4 cleanup 2.8453616 5 cleanup 1.1789683 6 ref 1.0140391 7

Hi Kevin, Are you saying that the quality is good at 20 ms and bad at 10 ms, or the reverse? Also, is this speech or music? What tool, what options? In general, it helps a lot if you post the sample (input and output). Cheers, Jean-Marc On 06/03/2016 12:48 PM, Kevin Connor wrote: > Hi Opus list, > > I'm noticing a discontinuity in the quality between use of 10ms and > 20ms

I have a file, each column of which is a separate year, and each row of each column is mean precipitation for that month. Looks like this (except it goes back to 1964). month X2000 X2001 X2002 X2003 X2004 X2005 X2006 X2007 X2008 X2009 1 1.600 1.010 4.320 2.110 0.925 3.275 3.460 0.675 1.315 2.920 2 2.960 3.905 3.230 2.380 2.720 1.880 2.430 1.380

Dear colleagues, How can I do to "relevel" the intercept? I need that the treatment "Db" be the intercept, and have p-values for the comparisons with the others treatments. I used the function "relevel" but it did not work out to have what I want. Thanks for your help, Xavier T1 <- read.table(file.choose(), h=T) > head(T1) treatment replicate Time

Buenos días, Necesito calcular la vida media de cada uno de nuestros modelos de producto pero tengo un histórico incompleto (para los productos más nuevos tengo la vida completa de las cohortes, pero para los más antiguos tengo sólo la parte final de la vida de las cohortes). He decidido calcular la esperanza de vida dinámica con un modelo actuarial, concretamente la librería 'demography'

I have a challenge that I want to share with the group. This is not homework (but I may assign it as such if I teach the appropriate class again) and I have found one solution, so don't need anything urgent. This is more for fun to see if others can find a better solution than I did. The challenge: I want to read a book in a given number of days. I want to read an integer number of

Also from my observation, based on network packets and time measurements, it seems the CIFS clients haven't done any sort of cache. For example, doing a "ls" for 5 times on the same folder within a short period of time. The network packet sizes are almost equal every time and the time it takes is similar. Isn't there supposed to be some page cache or dentry cache that could

Hi Jean-Marc, Sorry for late reply, thanks for interest. It's quality good for 10ms/audio, poorer for 20ms/audio. Quality equivalent for 10,20ms for mode=voip. PESQ was the tool that alerted me to something of interest, but I don't trust PESQ to almost any degree! It's good for hearing relative differences, of course, but not absolutes. Bitrate here was 28kbps, but I hear

Two problems with the code below. A. It produces empty JPEGs. When the 'bwplot' line alone is submitted, the plot duly shows up. B. When the 'bwplot' line alone is submitted, y labels are values 1 to 6, not actual distinct values of y$maxthreads. (C. I would, of course, prefer to produce plots for all distinct values of x$maxthreads in a single swoop, on a single figure). Can

R Help - I'm trying to run a correlation matrix with a covariate of "age" and will at some point will also want to covary other variables concurrently. I'm using the "psych" package and have tried other methods such as writing a loop to extract semi-partial correlations, but it does not seem to be working. How can I accomplish this? library(psych) > set.cor(y =

Dear useRs, I am trying to model a time series with a transfer function. I think it can be put into the ARMA framework, and estimated with the 'arima' function (and others have made similar comments on this list). I have tried to do that, but the results have so far been disappointing. Maybe I am trying to make 'arima' do something it can't... The data are time series of

Hi, I am trying to find m breakpoints of a linear regression model. I used the segmented package. It works fine for small number of predicators and breakpoints.(3 r.v. 3 points). However, my model has 14 variables it even would not work even for just one breakpoints!. The error message is always estimated breakpoints are out of range. Since my problem is time related problem. So I

Are these 225 compile time regressions real? It sure looks bad! Ciao, Duncan. On 01/12/11 09:39, llvm-testresults at cs.uiuc.edu wrote: > > bwilson__llvm-gcc_PROD__i386 nightly tester results > > URL http://llvm.org/perf/db_default/simple/nts/380/ > Nickname bwilson__llvm-gcc_PROD__i386:4 > Name curlew.apple.com > > Run ID Order Start Time End Time > Current 380

Dear arun and all R users, I will first of all try to simply define my issue.. I have data in the following format Year Discharge dd/mm/yyyy x .. … … … There are some NA values in the discharge which I would like to predict by using “predict command”. I cant figure out the way to write the coding for that. Could you please help me on that??? I have also ,written