similar to: Calculating number of elapsed days from starting date

Hello, I have longitudinal data of the form below from N subjects; I am trying to create figure with N small subplots on a single page, in which each plot is from only one subject, and in each plot there is a separate curve for each value of param1. So in this case, there would be four plots on the page (one each for Bob, Steve, Kevin and Dave), and each plot would have two separate curves (one

Hi Guys, stumped by a simple problem. I would like to take a file of the form Pair group param1 1 D 10 1 D 10 1 R 10 1 D 10 2 D 10 2 D 10 2 D 10 2 R 10 2 R 10 etc.. and for each pair, calculate the average of

Hello, I have a data frame containing time (e.g. GMT), and I would like to create/add a new variable that would be the computation of the elapsed time since the first observation. Does anyone have a suggestion for an easy way to do this? I am having trouble creating a new variable that would contain just the first time observation (then I could take difference between actual time and

I spent some time on this simple question, also searched the forum, eventually hacked my way to an ugly solution for my particular problem but I would like to improve my coding: I have data of the form: df <- expand.grid(group=c('copper', 'zinc', 'aluminum', 'nickel'), condition1=c(1:4)) I would like to add a new data column "condition2", with values

Hi all, I have a short R code file that I am using to perform calculations on a dataset. I am having a few issues with output: 1. Although my input data file is 2149 lines long, when I type "results.df" from the command line, I get the appropriate calculation results for only the first 46 rows. Same result if I "sink" the output to a file, and type "results.df" at

I have a dataset of the form below, consisting of one unique ID per row, followed by a series of visit dates. At each visit there are values for 3 dichotomous variables. Of the 8 different possible combinations of the three variables, 4 are "abnormal" and the remaining 4 are "normal". Everyone starts out abnormal, and then either continues to be abnormal at subsequent visits,

Hi all, I got this time for my code, > proc.time()-pt user system elapsed 132541.743 0.004 132533.526 As you can see, there is huge difference btw elapsed time and system time. Does that mean lots of I/O? Or some bad coding? Thanks, Libo [[alternative HTML version deleted]]

https://bugzilla.samba.org/show_bug.cgi?id=11382 Bug ID: 11382 Summary: elapsed time calculation does not account for time function possibly returning -1 Product: rsync Version: 3.1.1 Hardware: All OS: All Status: NEW Severity: normal Priority: P5 Component: core

How do I post text-string dates along the x-axis instead of the excel_date position values? I would like to plot a time-series of chemical values changing with time The first column is the internal date from excel. This should be the x-axis position of a graph of the plotted data. The second column is a text-string of date. This should be what is posted (instead of the excel_date). The third

Hi again, I keep posting about my problem with HTB -> http://mailman.ds9a.nl/pipermail/lartc/2005q3/016611.html With a bit of search I recently found the exact same problem I have in the 2004 archives with some graphs that explain it far better than I did -> http://mailman.ds9a.nl/pipermail/lartc/2004q4/014519.html and http://mailman.ds9a.nl/pipermail/lartc/2004q4/014568.html

I am perplexed about NOTEs I get from Win Builder on my genridge package, https://github.com/friendly/genridge. It shows, e.g., Examples with CPU or elapsed time > 10s user system elapsed plot3d.ridge 12.4 0.05 12.45 However, if I run *exactly the same code* in my console with system.time(), I get user system elapsed 0.95 0.16 1.17 What could be the explanation for

Hi all, I need to be able to determining the elapsed time of a call. I tried commands like 'show channel' or 'zap show channel', this outputs a list of parameters including 'elapsed time' but for some reason this is always '0h0m0s'. Is this normal or am I looking at the wrong place or using the wrong command? My configuration: Asterisk 1.0.7 + Bristuffed The

Hi, I have an input data > dput (input) structure(list(ScanDate = structure(c(16433, 16440, 16447, 16454, 16461, 16468, 16475, 16482, 16489, 16496, 16503, 16510, 16517, 16524, 16531, 16538, 16545, 16552, 16559, 16566, 16573, 16580, 16587, 16594, 16601, 16608, 16615, 16622), class = "Date"), OnPromotion = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 0, 0, 0, 1,

Hi, I have tab-delimited data with an unequal number of entries per column, of the sort: A B C 1 2 2 3 4 1 5 2 2 6 2 5 2 3 6 2 I would like to make a histogram of the frequencies of each represented number in a "stacked" histogram, where you can see the contribution of each group (A, B or C) to the total height of the bar, and each bar labeled with the

Hello, I am currently using R to run an external program and then read the results the external program sends to the stdout which are tsv data. When R reads the results in it converts it to to a list of strings which I then have to maniuplate with a whole slew of commands (which, figuring out how to do was a reall challenge for a newbie like myself)--see below. Here's the code I'm

Hello, I am new to R and am having difficulty formatting numerical output from a regression analysis. My code iteratively performs linear regression on a dataset while excluding certain data ranges. My code: rm(list = ls(all = TRUE)) sink("outfile") dat <- read.table("testdat", sep="\t", header=TRUE) int = 0.2 for (x in c(0:20)) { subdat <- subset(dat, time

I am working with some large text files (up to 16 GBytes). I am interested in extracting the words and counting each time each word appears in the text. I have written a very simple R program by following some suggestions and examples I found online. If my input file is 1 GByte, I see that R uses up to 11 GBytes of memory when executing the program on a 64-bit system running CentOS 6.3. Why is

Hello, I gather variants of this question have been asked previously. I have done some reading but only became more confused, as I suspect what I am trying to do is more basic than other applications. The following code readily calculates the difference in days between two dates: newdays <- ISOdate(2005, 5,12) - ISOdate(2006, 12, 22) However, I wanted to be able to deduct the dates in

Dear list, I am trying to find a fast solution to read moderately large (1 -- 10 million entries) text files containing only tab-delimited numeric values. My test file is the following, nr <- 1000 nc <- 5000 m <- matrix(round(rnorm(nr*nc),3),nr=nr) write.table(m, file = "a.txt", append=FALSE, row.names = FALSE, col.names = FALSE) scan() is faster than

Hi all, Since proc.time return three different kind of times (user, system and elapsed) , I am wondering which one is right for calculating flops. In New S Language (Becker et. al. ) , it seems to be the user because " the user time measures the processor time used in S and the system time measures the operating system in response to S's request". But in R Help , system time