From dmurdoch at pair.com  Tue Feb  3 14:32:44 2004
From: dmurdoch at pair.com (Duncan Murdoch)
Date: Tue Feb  3 14:33:54 2004
Subject: [Rd] request for comments --- package "distr" --- S4 Classes for
	Distributions
In-Reply-To: <x2ptcw2w1n.fsf@biostat.ku.dk>
References: <D7A3CFD7825BD6119B880002A58F06C20680ADF6@groexmb02.pfizer.com>
	<x2ad413yue.fsf@biostat.ku.dk> <401F6DD0.2080602@uni-bayreuth.de>
	<7b2v1018thc0oecs1sdq1rm447cvlmag5f@4ax.com>
	<x2ptcw2w1n.fsf@biostat.ku.dk>
Message-ID: <hf8v10lfmafc8h4a7aboqaial6k3h72prs@4ax.com>

On 03 Feb 2004 13:21:24 +0100, Peter Dalgaard
<p.dalgaard@biostat.ku.dk> wrote :

>Duncan Murdoch <dmurdoch@pair.com> writes:

>> That's the most common 1-dimensional singular distribution, but higher
>> dimensional distributions are much more commonly singular.  For
>> example, mixed continuous-discrete distributions, and other
>> distributions whose support is of lower dimension than the sample
>> space, e.g. X ~ N(0,1), Y=X.
>
>I don't think that qualifies as continuous, does it? Not in the sense
>that the distribution function is continuous, surely. 

Yes, for my second example the 2-d distribution function is
continuous, because there are no atoms:

F(x,y) = P(X <= x, Y <= y) = Phi(min(x,y))

I was wrong about the mixed case; sorry.

Duncan


[Rd] request for comments --- package "distr" --- S4 Classes for Distributions
Duncan Murdoch