[Rd] a new way to crash R? (PR#8981)

[ripley at stats.ox.ac.uk]

This works for me on both Linux and Windows.

Please check your memory usage: it does need about 900Kb of VM, and as you 
have less RAM than that installed you need to set --max-mem-size=1G or 
some such.

(It is quite likely that this is a Windows memory allocation failure: that 
has been reported before but not tracked down.)

On Wed, 14 Jun 2006, jritter at umn.edu wrote:

> This is a multi-part message in MIME format.
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> Dear R Team,
>
> First, thank you for incredibly useful software!
>
> Now the bad news:  The attached script (or the original version with
> real data) will reliably crash R on my machine.  I am using:
>
> R version: either 2.2.1 or 2.3.1
> Windows 2000 Professional, Service Pack 4
> 512 MB of RAM
>
> On my machine the script will crash R on line 42 [  probits21 <-
> lapply(...  ].
>
> In both this script and the "real" one, memory.size() indicates that R
> is about 512 MB just before executing the command that crashes it.  In
> other contexts, R has been able to allocate virtual memory on this
> computer without any trouble.
>
> Thanks again for all your work on R.
>
> Regards,
>
> Joe Ritter
>
> --------------------------------------------------------------------------
> Joseph A. Ritter
> Associate Professor
> Humphrey Institute of Public Affairs
> University of Minnesota
> Minneapolis, MN  55455
> U.S.A.
> 612-625-0442
>
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> name="crash.r"
> Content-Transfer-Encoding: 7bit
> Content-Disposition: inline;
> filename="crash.r"
>
> x1 <- rnorm(10000)
> x2 <- rnorm(10000)
> x3 <- rnorm(10000)
> x4 <- rnorm(10000)
> x5 <- rnorm(10000)
> x6 <- rnorm(10000)
> x7 <- rnorm(10000)
> x8 <- rnorm(10000)
> y <- round(runif(10000))
>
> specs <- list()
> specs$A <- formula(y~x1+x2+x3+x4+x5+x6+x7+x8)
> specs$B <- specs$A
> specs$C <- specs$A
> specs$D <- specs$A
> specs$E <- specs$A
> specs$F <- specs$A
> specs$H <- specs$A
> specs$I <- specs$A
> specs$J <- specs$A
>
> probits1 <- lapply(specs, glm, family=binomial(link="probit"))
> probits2 <- lapply(specs, glm, family=binomial(link="probit"))
> probits3 <- lapply(specs, glm, family=binomial(link="probit"))
> probits4 <- lapply(specs, glm, family=binomial(link="probit"))
> probits5 <- lapply(specs, glm, family=binomial(link="probit"))
> probits6 <- lapply(specs, glm, family=binomial(link="probit"))
> probits7 <- lapply(specs, glm, family=binomial(link="probit"))
> probits8 <- lapply(specs, glm, family=binomial(link="probit"))
> probits9 <- lapply(specs, glm, family=binomial(link="probit"))
> probits10 <- lapply(specs, glm, family=binomial(link="probit"))
> probits11 <- lapply(specs, glm, family=binomial(link="probit"))
> probits12 <- lapply(specs, glm, family=binomial(link="probit"))
> probits13 <- lapply(specs, glm, family=binomial(link="probit"))
> probits14 <- lapply(specs, glm, family=binomial(link="probit"))
> probits15 <- lapply(specs, glm, family=binomial(link="probit"))
> probits16 <- lapply(specs, glm, family=binomial(link="probit"))
> probits17 <- lapply(specs, glm, family=binomial(link="probit"))
> probits18 <- lapply(specs, glm, family=binomial(link="probit"))
> probits19 <- lapply(specs, glm, family=binomial(link="probit"))
> probits20 <- lapply(specs, glm, family=binomial(link="probit"))
> probits21 <- lapply(specs, glm, family=binomial(link="probit"))
> probits22 <- lapply(specs, glm, family=binomial(link="probit"))
> probits23 <- lapply(specs, glm, family=binomial(link="probit"))
> probits24 <- lapply(specs, glm, family=binomial(link="probit"))
> probits25 <- lapply(specs, glm, family=binomial(link="probit"))
> probits26 <- lapply(specs, glm, family=binomial(link="probit"))
> probits27 <- lapply(specs, glm, family=binomial(link="probit"))
> probits28 <- lapply(specs, glm, family=binomial(link="probit"))
> probits29 <- lapply(specs, glm, family=binomial(link="probit"))
> probits30 <- lapply(specs, glm, family=binomial(link="probit"))
> probits31 <- lapply(specs, glm, family=binomial(link="probit"))
>
> --------------010500030900050501010804--
>
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-- 
Brian D. Ripley,                  ripley at stats.ox.ac.uk
Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
University of Oxford,             Tel:  +44 1865 272861 (self)
1 South Parks Road,                     +44 1865 272866 (PA)
Oxford OX1 3TG, UK                Fax:  +44 1865 272595