Thread View: sci.math.stat
3 messages
3 total messages
Started by Luke Whitaker
Fri, 20 Nov 1992 12:58
Calculating variances
Author: Luke Whitaker
Date: Fri, 20 Nov 1992 12:58
Date: Fri, 20 Nov 1992 12:58
17 lines
1073 bytes
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
Author: Roy St. Laurent
Date: Fri, 20 Nov 1992 15:47
Date: Fri, 20 Nov 1992 15:47
37 lines
2155 bytes
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
Author: Gary McClelland
Date: Fri, 20 Nov 1992 21:39
Date: Fri, 20 Nov 1992 21:39
22 lines
1476 bytes
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
Thread Navigation
This is a paginated view of messages in the thread with full content displayed inline.
Messages are displayed in chronological order, with the original post highlighted in green.
Use pagination controls to navigate through all messages in large threads.
Back to All Threads