[R] Matrix oriented computing

[John Fox]

Dear Mark,

For that matter, the loop isn't a whole a slower (on my 3GHz Win XP system):

> x <- c(0.005, 0.010, 0.025, 0.05, 0.1, 0.5, 0.9, 0.95, 0.975, 0.99, 0.995)
> df <- 1:1000
> system.time(mat <- sapply(x, qchisq, df), gcFirst = TRUE)
[1] 0.08 0.00 0.08   NA   NA
> 
> mat <- matrix(0, 1000, 11)
> system.time(for (i in 1:length(df)) mat[i,] <- qchisq(x, df[i]))
[1] 0.09 0.00 0.10   NA   NA
> 

Regards,
 John

--------------------------------
John Fox
Department of Sociology
McMaster University
Hamilton, Ontario
Canada L8S 4M4
905-525-9140x23604
http://socserv.mcmaster.ca/jfox 
-------------------------------- 

> -----Original Message-----
> From: r-help-bounces at stat.math.ethz.ch 
> [mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of Marc 
> Schwartz (via MN)
> Sent: Friday, August 26, 2005 10:26 AM
> To: Peter Dalgaard
> Cc: r-help at stat.math.ethz.ch
> Subject: Re: [R] Matrix oriented computing
> 
> On Fri, 2005-08-26 at 15:25 +0200, Peter Dalgaard wrote:
> > Marc Schwartz <MSchwartz at mn.rr.com> writes:
> > 
> > > x <- c(0.005, 0.010, 0.025, 0.05, 0.1, 0.5, 0.9, 
> > >        0.95, 0.975, 0.99, 0.995)
> > > 
> > > df <- c(1:100)
> > > 
> > > mat <- sapply(x, qchisq, df)
> > >
> > > > dim(mat)
> > > [1] 100  11
> > >  
> > > > str(mat)
> > >  num [1:100, 1:11] 3.93e-05 1.00e-02 7.17e-02 2.07e-01 
> 4.12e-01 ...
> > 
> > outer() is perhaps a more natural first try... It does give the 
> > transpose of the sapply approach, though.
> > 
> > round(t(outer(x,df,qchisq)),2)
> > 
> > should be close. You should likely add dimnames.
> 
> 
> 
> What I find interesting, is that I would have intuitively expected
> outer() to be faster than sapply().  However:
> 
> 
> >  system.time(mat <- sapply(x, qchisq, df), gcFirst = TRUE)
> [1] 0.01 0.00 0.01 0.00 0.00
>  
> >  system.time(mat1 <- round(t(outer(x, df, qchisq)), 2),
>                gcFirst = TRUE)
> [1] 0.01 0.00 0.01 0.00 0.00
>  
> # No round() or t() to test for overhead
> >  system.time(mat2 <- outer(x, df, qchisq), gcFirst = TRUE)
> [1] 0.01 0.00 0.02 0.00 0.00
> 
> 
> # Bear in mind the round() on mat1 above
> > all.equal(mat, mat1)
> [1] "Mean relative  difference: 4.905485e-05"
> 
> > all.equal(mat, t(mat2))
> [1] TRUE
> 
> 
> Even when increasing the size of 'df' to 1:1000:
> 
> 
> >  system.time(mat <- sapply(x, qchisq, df), gcFirst = TRUE)
> [1] 0.16 0.01 0.16 0.00 0.00
> 
> >  system.time(mat1 <- round(t(outer(x, df, qchisq)), 2), gcFirst =
> TRUE)
> [1] 0.16 0.00 0.18 0.00 0.00
>  
> >  # No round() or t() to test for overhead
> >  system.time(mat2 <- outer(x, df, qchisq), gcFirst = TRUE)
> [1] 0.16 0.01 0.17 0.00 0.00
> 
> 
> 
> It also seems that, at least in this case, t() and round() do 
> not add much overhead.
> 
> Best regards,
> 
> Marc
> 
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