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- Newsgroups: sci.math.stat
- Path: sparky!uunet!munnari.oz.au!manuel!news
- From: Andrew.Robinson@anu.edu.au
- Subject: Re: Degrees of Freedom Was: Re: Standard Deviation.
- Message-ID: <1992Aug21.000314.2367@newshost.anu.edu.au>
- Sender: news@newshost.anu.edu.au
- Organization: Australian National University
- References: <1992Aug14.172833.11844@cbfsb.cb.att.com> <c48nbgtf@csv.warwick.ac.uk> <WVENABLE.92Aug18180002@algona.stats.adelaide.edu.au> <1992Aug18.214711.6657@mailhost.ocs.mq.edu.au> <l95552INNa4h@roundup.crhc. <thompson.714338397@kiyotaki.econ.umn.edu>
- Date: Fri, 21 Aug 92 00:03:14 GMT
- Lines: 49
-
- In article <thompson.714338397@kiyotaki.econ.umn.edu>
- thompson@atlas.socsci.umn.edu (T. Scott Thompson) writes:
- >hougen@uirvlh.csl.uiuc.edu (Darrell Roy Hougen) writes:
- >
- [deletia]
- >
- >I have never been very satisfied with this notion of "degrees of
- >freedom" being equivalent to "pieces of independent information". The
- >correspondence works well enough for linear models and independent
- >observations, as in the example given, but there are alternative
- >interpretations (in terms of the dimension of orthogonal subspaces)
- >that do just as well in this setting.
- >
- >To put out a concrete example that illustrates the nature of my
- >qualms, consider the following. Suppose my data consist of a single
- >number, say X. Suppose that I am given two pieces of information
- >about X (but not X itself):
- >
- > (1) I can observe Y := X**2
- > (2) I can observe Z := { 1 if X > 0
- > { -1 otherwise
- >
- >How many "pieces of information" do I now have? Clearly I can recover
- >X from Y and Z by the formula X = Z * <positive square root of Y>, but
- >neither Y nor Z alone suffices (excluding the special case where
- >X = Y = 0). Thus Y and Z must each "use up" (at least) one degree of
- >freedom in the usual accounting. Thus I must conclude that
- >
- > <degrees of freedom in X> .GE. 1 + 1 = 2.
- >
- >For obvious reasons I do not find this to be an acceptable answer!
- >What do you think? What am I missing? Is there any meaningful
- >interpretation to "degrees of freedom" in a general theory of
- >inference?
-
- I'm going to go _way_ out on a limb here and say that I think that you have
- _one_ piece of infomation. If you don't have X then your data doesn't consist
- of a single number, it consists of a single observation from which you have
- measured a two variable vector - [Y,Z]. You know that there is an X and you
- want to use Y and Z to estimate it using a predetermined model, which you have
- specified. This seems to me to be a non-straightforward case of a multivariate
- regression, with two dependent variables and one observation.
-
- Comments?
-
- regardless,
- Andrew
-
- now hit d
-