similar to: [R] par(uin)

Hi, I've been trying to use several plotting routings that make use of S's par("uin"), the number of user units per inch. For the moment I've substituted all of the occurences of this with par.uin _ function() (par("fin") / c( diff(par("xaxp")[1:2]),diff(par("yaxp")[1:2]))) This seems to work fine for my needs. -Greg

I run Win2000, and when I try to write to a file and later use it it seems that R 1.02.0 has a firm grip on it: > version _ platform i386-pc-mingw32 arch x86 os Win32 system x86, Win32 status major 1 minor 2.0 year 2000 month 12 day 15

Funnily enough, it seems that adjustment of text in the verical direction is more flexible than in the horizontal. Horizontal adjustment parameters, seem to be set to the closest of 0 and 1 if they fall outside (0,1). Try e.g.: plot(0:1,0:1) for (a in seq(-5,5,0.5) ) text(0.5, 0.5, "Y", adj=c(0,a), cex=2, col="red" ) for (a in seq(-5,5,0.5) ) text(0.5, 0.5, "X",

Running R : Copyright 1999, The R Development Core Team Version 0.90.1 (December 15, 1999) on NT 4.0 gives me problems with: win.metafile(file="./x.emf") x <- 1:100/7 plot(x,cos(x),type="n") lines(x,sin(x)) abline(v=0:15,h=-2:2/2,col=gray(0.8)) Only labels and titles on axes are in the file. No axes or lines of any kind. (I look at the file by inserting it in Word,

To the R developers, The discussion below reminded me that I think it might be a good idea to take the Relevel function from the Lexis package and replace relevel in stats with it. This is really nothing special for epidemiology. It is fully compatible with the existing relevel (it actually contains the relevel code almost verbatim as a subset), but it has the extra functionality of combining

The date library contains a function date.mdy that converts a number D to the date (month,date,year as a list) at D days after 1 Jan 1960. This a convention that fits in with SASs. The logic would be that the result was the date at D days after 1 Jan 1960 00:00:00 (which is a POINT in time as opposed to a date which is an interval), so that any D with 2<=D<3 was rounded to 3 Jan 1960 and

Did not seem to reach Saikat DebRoy, this might be the forum. Bendix -----Original Message----- From: BXC (Bendix Carstensen) Sent: 24. november 2008 15:00 To: 'saikat at stat.wisc.edu'; 'stvjc at channing.harvard.edu' Subject: read.ssd It's always annoyed me that that read.ssd crashed on datasets with long variable names, but the other day a collegue of mine pointed out to

I have an odd problem in building a package with only R-code in it. I have a package mainly used by myself which I last build under R 1.9.0. The operation system is Win2000 5.00.2195, Service Pack 3 When I do: c:\stat\r\rw2000\bin\Rcmd install --docs=normal --build --library=c:\stat\R\bxc\library c:\stat\R\bxc\library.sources\xx then after updating help pages I get: preparing package xx for

I have an odd problem in building a package with only R-code in it. I have a package mainly used by myself which I last build under R 1.9.0. The operation system is Win2000 5.00.2195, Service Pack 3 When I do: c:\stat\r\rw2000\bin\Rcmd install --docs=normal --build --library=c:\stat\R\bxc\library c:\stat\R\bxc\library.sources\xx then after updating help pages I get: preparing package xx for

A funny thing happened when I wanted a student of mine to install Brugs. Using the InstallPackages in the windows version, firts gives an erro, but trying again works flawlessly. R version is 2.7.0 on WinXP. Any explanation? Bendix Carstensen ______________________________________________ Bendix Carstensen Senior Statistician Steno Diabetes Center Niels Steensens Vej 2-4 DK-2820 Gentofte

This is how I get the month names from within R: > mon <- rep(strptime("01/01/1952", format = "%d/%m/%Y"), 12) > mon$mon <- mon$mon + 0:11 > mnam <- months(mon, abbreviate = F) > mnam [1] "januar" "februar" "marts" "april" "maj" "juni" "juli" "august"

As a sequel to my previous mail on cut, formatC does not produce what I have been taught is significant digits: > x <- c(1.0793,1.0796, 11.0954, 11.0736 ) > formatC(x,digits=3,format="g") [1] "1.08" "1.08" "11.1" "11.1" (3,3,3,3) significant digits OK > formatC(x,digits=3,format="f") [1] "1.079"

Tha handy thinb about the fig=TRUE option in Sweave is that you do not have to bother about filenames and starting and stpping the device. I want the the resulting LaTeX to look as: \begin{Schunk} \begin{Sinput} > x <- seq(-2 * pi, 2 * pi, 0.1) > plot(x, cos(x), type = "l", lwd = 4) \end{Sinput} \end{Schunk} \begin{figure} \includegraphics[width=0.6\textwidth]{xx-001}

Consider the following two specifications of a model: library( splines ) x <- 1:100 y <- rnorm( 100 ) w <- rep( 1, 100 ) A <- factor( sample( 1:2, 100, replace=T ) ) B <- factor( sample( letters[1:4], 100, replace=T ) ) summary( lm( y ~ ns( x, knots=c(30, 50, 70 ), intercept=T ):A - 1 + B ) ) summary( lm( y ~ ns( x, knots=c(30, 50, 70 ), intercept=T ):A - 1 + B:w ) ) The

There is now an Epi-package on CRAN. It is intended for epidemiological analysis in R. It has its own homepage, http://www.pubhealth.ku.dk/~bxc/Epi The package has been used at the course "Statistical practise in Epidemiology with R", see http://www.pubhealth.ku.dk/~bxc/SPE. A mailing list for people using R for epidemiology, R-sig-Epi, has been set up, see

A new major upgrade of the Epi package for Epidemiological data analysis has been put on CRAN, it is now at version 1.0.7. It contains an entirely new way of representing follow-up data on multiple timescales and multiple states. See the function Lexis(). Plus a lot of other useful stuff for epidemiological analysis. See more on the package homepage, www.biostat.ku.dk/~bxc/Epi Note also that

There is now an Epi-package on CRAN. It is intended for epidemiological analysis in R. It has its own homepage, http://www.pubhealth.ku.dk/~bxc/Epi The package has been used at the course "Statistical practise in Epidemiology with R", see http://www.pubhealth.ku.dk/~bxc/SPE. A mailing list for people using R for epidemiology, R-sig-Epi, has been set up, see

In my 1021-version I get: > version _ platform i386-pc-mingw32 arch x86 os Win32 system x86, Win32 status major 1 minor 2.1 year 2001 month 01 day 15 language R > as.POSIXct( "1970/01/01" ) [1]

Further to the discussion between Murray Jorgensen and Brian Ripley, it seems to me better to choose tabulations that will not come and bite you. Suppose your data are sligtly irregular, e.g. (for the sake of the argument): data( warpbreaks ) warpbreaks$variant <- rep( 1:5, len=54 ) attach( warpbreaks ) tb <- table( wool, tension, variant ) tb # in this case you would like to see: tp

Further to the discussion between Murray Jorgensen and Brian Ripley, it seems to me better to choose tabulations that will not come and bite you. Suppose your data are sligtly irregular, e.g. (for the sake of the argument): data( warpbreaks ) warpbreaks$variant <- rep( 1:5, len=54 ) attach( warpbreaks ) tb <- table( wool, tension, variant ) tb # in this case you would like to see: tp