how R implement qnorm()

Thanks a lot. It's very helpful.
I've read through the c code. Just FYI and for my completion of the
question, I post some of my thought on it:
To me it looks like the algorithm is actually inquiring through an
approximation table (the approximations, at least for pnom, is "derived
from those in "Rational Chebyshev approximations for the error function" by
W. J. Cody, Math. Comp., 1969, 631-637."), it is not using any function
such as intergration or inverse erf to compute the value based on an
equation as I thought, though lack a bit subtlety but the up side is the
speed.

From the point of view of R, the only relevant issues are precision,

Hope this can help others who had similar questions as well.

Sheng


On Thu, Oct 18, 2012 at 2:32 AM, peter dalgaard <pdalgd at gmail.com> wrote:

On Oct 18, 2012, at 09:55 , Prof Brian Ripley wrote:

R is a bit confusing as it requires inverse error function (X =
- sqrt(2)* erf-1 (2*P)), while R doesn't have a build in one. The InvErf
function most people use is through qnorm( InvErf=function(x)

I think you are wrong about 'most people': this is the notation used by

a small group of non-statisticians (mainly physicists, I think).

Well, he's right in the sense that it is erf/erfc that are commonly
documented in collections of special functions (like Abramowitz & Stegun),
and also those that appear in common C math libraries. In both cases of
course because physicists have dominated in their development.

Of course "most people" use Excel these days (which has the inverse normal
distribution but AFAICS not the inverse error function).

--
Peter Dalgaard, Professor,
Center for Statistics, Copenhagen Business School
Solbjerg Plads 3, 2000 Frederiksberg, Denmark
Phone: (+45)38153501
Email: pd.mes at cbs.dk  Priv: PDalgd at gmail.com

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