Hello, and please excuse this off-topic question, but I have not been
able to find an answer elsewhere. Consider a value Z that is calculated
using the product (or ratio) of two means X_mean and Y_mean:
Z=X_mean*Y_mean. More generally, Z=f(X_mean, Y_mean). The standard
error of Z will be a funct
You could try googling for "delta method". I believe MASS even has code for
that...
Andy
> From: Bill Shipley
>
> Hello, and please excuse this off-topic question, but I have not been
> able to find an answer elsewhere. Consider a value Z that is
> calculated
> using the product (or ratio) of
I know two standard ways to approach this. The traditional
approximation is called the "delta method"; it uses a Taylor series
approximation, usually of first order but could be higher. Googling for
"delta method" produced several useful hits just now. The second method
is Monte Carlo.
Hi, Andy:
MASS4 has section 5.7 "Bootstrap and Permutation Methods". Is
this what you are suggesting? It certainly is relevant to the question
(but not to the "delta method", except as a means of checking on it).
Thanks,
spencer graves
Liaw, Andy wrote:
You could try googling
What I have in mind is the discussion on pp. 167-172 of `S Programming'.
Cheers,
Andy
> From: Spencer Graves
>
> Hi, Andy:
>
> MASS4 has section 5.7 "Bootstrap and Permutation Methods". Is
> this what you are suggesting? It certainly is relevant to
> the question
> (but not to the "
Liaw, Andy wrote:
You could try googling for "delta method". I believe MASS even has code for
that...
Andy
If you have the original data you can bootstrap --- else you need the
standar errors and
correlation between the means, and can use the delta methos as above.
You could even
use D or der
Liaw, Andy wrote:
You could try googling for "delta method". I believe MASS even has code for
that...
Andy
also,
help.search("delta")
does give nothing usefull, so if it is in MASS it would be hidden, and
need a \concept
entry in the .Rd file.
The delta method is really nothimg more (or less)
Bill,
P. 146 of Casella and Berger's "Statistical Inference" 1990 starts a
section on bivariate transformations.
Andrew
--
Andrew Robinson Ph: 208 885 7115
Department of Forest Resources Fa: 208 885 6226
University of Idaho E : [EMAIL PROTECTED]
PO Box
On Wed, 5 Jan 2005, Kjetil Brinchmann Halvorsen wrote:
Liaw, Andy wrote:
You could try googling for "delta method". I believe MASS even has code
for
that...
I believe you are thinking of an example in S Programming, which does
automatic differentiation and the delta method.
-thomas
Bill Shipley wrote:
Hello, and please excuse this off-topic question, but I have not been
able to find an answer elsewhere. Consider a value Z that is calculated
using the product (or ratio) of two means X_mean and Y_mean:
Z=X_mean*Y_mean. More generally, Z=f(X_mean, Y_mean). The standard
error
Of course, the delta method is terrible when the first derivative
is small relative to the curvature. In that case, you either need to
consider bootstrap, Monte Carlo, permutation testing, as suggested by
Venables and Ripley in MASS and S Programming, or possibly using a
higher order Tayl
11 matches
Mail list logo
