# [Rd] Inaccurate complex arithmetic of R (Matlab is accurate)

Mon Aug 3 18:00:50 CEST 2009

```Dear Martin,

Thank you for this useful trick.  However, we are interested in a "general"
approach for exact derivative computation.  This approach should allow the
user to specify the mathematical function that needs to be differentiated in
"any" form that the user chooses.  So, your trick will be difficult to
implement there.  Furthermore, do we know for sure that `exponentiation' is
the only operation that results in inaccuracy?  Are there other operations
that also yield inaccurate results for complex arithmetic?

Hans Borchers also checked the computations with other free numerical
software, such as Octave, Scilab, Euler, and they all return exactly the
same results as Matlab.  It would be a shame if R could not do the same.

It would be great if the R core could address the "fundamental" issue.

Thank you.

Best regards,
Ravi.

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Assistant Professor, The Center on Aging and Health

Division of Geriatric Medicine and Gerontology

Johns Hopkins University

Ph: (410) 502-2619

Fax: (410) 614-9625

Webpage:
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-----Original Message-----
From: Martin Becker [mailto:martin.becker at mx.uni-saarland.de]
Sent: Monday, August 03, 2009 5:50 AM
Cc: r-devel at stat.math.ethz.ch; hwborchers at googlemail.com
Subject: Re: [Rd] Inaccurate complex arithmetic of R (Matlab is accurate)

Dear Ravi,

the inaccuracy seems to creep in when powers are calculated. Apparently,
some quite general function is called to calculate the squares, and one can
avoid the error by reformulating the example as follows:

rosen <- function(x) {
n <- length(x)
x1 <- x[2:n]
x2 <- x[1:(n-1)]
sum(100*(x1-x2*x2)*(x1-x2*x2) + (1-x2)*(1-x2)) }

x0 <- c(0.0094, 0.7146, 0.2179, 0.6883, 0.5757, 0.9549, 0.7136, 0.0849,
0.4147, 0.4540) h <- c(1.e-15*1i, 0, 0, 0, 0, 0, 0, 0, 0, 0) xh <- x0 + h

rx <- rosen(xh)
Re(rx)
Im (rx)

I don't know which arithmetics are involved in the application you
mentioned, but writing some auxiliary function for the calculation of x^n
when x is complex and n is (a not too large) integer may solve some of the
numerical issues. A simple version is:

powN <- function(x,n) sapply(x,function(x) prod(rep(x,n)))

The corresponding summation in 'rosen' would then read:

sum(100*powN(x1-powN(x2,2),2) + powN(1-x2,2))

HTH,

Martin

> Dear All,
>
> Hans Borchers and I have been trying to compute "exact" derivatives in R
using the idea of complex-step derivatives that Hans has proposed.  This is
a really, really cool idea.  It gives "exact" derivatives with only a
minimal effort (same as that involved in computing first-order
forward-difference derivative).
>
> Unfortunately, we cannot implement this in R as the "complex arithmetic"
in R appears to be inaccurate.
>
> Here is an example:
>
> #-- Classical Rosenbrock function in n variables rosen <- function(x)
> { n <- length(x)
> x1 <- x[2:n]
> x2 <- x[1:(n-1)]
> sum(100*(x1-x2^2)^2 + (1-x2)^2)
> }
>
>
> x0 <- c(0.0094, 0.7146, 0.2179, 0.6883, 0.5757, 0.9549, 0.7136,
> 0.0849, 0.4147, 0.4540) h <- c(1.e-15*1i, 0, 0, 0, 0, 0, 0, 0, 0, 0)
> xh <- x0 + h
>
> rx <- rosen(xh)
> Re(rx)
> Im (rx)
>
> #  rx = 190.3079796814885 - 12.13915588266717e-15 i  # incorrect
> imaginary part in R
>
> However, the imaginary part of the above answer is inaccurate.  The
correct imaginary part (from Matlab) is:
>
> 190.3079796814886 - 4.66776376640000e-15 i  # correct imaginary part
> from Matlab
>
> This inaccuracy is serious enough to affect the acuracy of the compex-step
>
> Hans and I were wondering if there is a way to obtain accurate "small"
imaginary part for complex arithmetic.
>
> I am using Windows XP operating system.
>
> Thanks for taking a look at this.
>
> Best regards,
> Ravi.
>
>
> ____________________________________________________________________
>
> Assistant Professor,
> Division of Geriatric Medicine and Gerontology School of Medicine
> Johns Hopkins University
>
> Ph. (410) 502-2619
>
> ______________________________________________
> R-devel at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-devel
>

--
Dr. Martin Becker
Statistics and Econometrics
Saarland University
Campus C3 1, Room 206
66123 Saarbruecken
Germany

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