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3 total messages Started by Luke Whitaker Fri, 20 Nov 1992 12:58
Calculating variances
#710
Author: Luke Whitaker
Date: Fri, 20 Nov 1992 12:58
17 lines
1073 bytes
I am trying to develop some ideas around contingency tables and entropy, 
and have come up with some measures which I think are quite useful,
but the problem is that I have no idea in general how to compute variances for
these measures. 

It seems that the only general rule for computing variances is for the sum or
difference of random variables (ie var(x+/-y) = var(x) + var(y)). What about 
products, reciprocals and other arbitrary combinations of random variables. 
I realise that this is non-trivial and that there is no simple answer as 
there is for sums and differences but there must be techniques to get a 
handle on this.

Could someone point me in the right direction, references etc for this problem.

thanks,

Luke
Re: Calculating variances
#711
Author: Roy St. Laurent
Date: Fri, 20 Nov 1992 15:47
37 lines
2155 bytes
In article <luke.722264309@barney>, luke@cs.city.ac.uk (Luke Whitaker) writes:
|> 
|> It seems that the only general rule for computing variances is for the sum or
|> difference of random variables (ie var(x+/-y) = var(x) + var(y)). What about 
|> products, reciprocals and other arbitrary combinations of random variables. 
|> I realise that this is non-trivial and that there is no simple answer as 
|> there is for sums and differences but there must be techniques to get a 
|> handle on this.
|> 
|> Could someone point me in the right direction, references etc for this problem.

An approximate answer to your question is given by the delta-method -- a method
for finding the asymptotic variance of f(x) for some smooth function f(.), as a 
function of var(x).
   In the simplest case, the delta method gives:
         approx var(f(x)) = f'(mu)^2 var(x)   
where f'(mu) is the first derivative of f evaluated at mu=E(x).
    For ratios of random variables and other functions, a more general 
(multivariate) version of the delta method may be used.  See either of the
references below for the details.
   
Ref'ns
  Bishop,YMM, Fienberg,SE, & Holland, PW (1975).  Discrete Multivariate Analysis:
Theory and Practice.  MIT Press: Cambridge, Mass. p486-502. 
  Serfling, RJ (1980).  Approximation Theorems of Mathematical Statistics.  Wiley:
New York.

 -- Roy St. Laurent
    Biostatistics
    Univ. of Mich.
    roy@sol.biostat.med.umich.edu
-- 
  -- Roy St. Laurent (roy@biostat.med.umich.edu)

"Even $10 calculators have sigma buttons.  [I] haven't seen one with an 
 M-estimator button, yet."         --Jerry Dallal in sci.math.stat
Re: Calculating variances
#714
Author: Gary McClelland
Date: Fri, 20 Nov 1992 21:39
22 lines
1476 bytes
luke@cs.city.ac.uk (Luke Whitaker) writes:

>It seems that the only general rule for computing variances is for the sum or
>difference of random variables (ie var(x+/-y) = var(x) + var(y)). What about 
>products, reciprocals and other arbitrary combinations of random variables. 
>I realise that this is non-trivial and that there is no simple answer as 
>there is for sums and differences but there must be techniques to get a 
>handle on this.

>Could someone point me in the right direction, references etc for this problem.

A useful ref on the variance (and covariance) of products is

Bohrnstedt, G.W., \& Goldberger, A.S. (1969).  On the
exact covariance of products of random variables.  {\it Journal of the
American Statistical Association, 64}, 1439--1442.

They cite earlier work by Goodman which is also quite useful.

gary mcclelland
univ of colorado
mcclella@yertle.colorado.edu
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