Steve:
A not very fancy sollution is to loop over the rows and the columns, like the example code below.
HTH,
Maarten
*---------------begin example-----------
sysuse auto, clear
recode rep78 1=3 2=3
tab rep78 foreign, matcell(Cell)
matrix Proportions = Cell/r(N)
local r = rowsof(Proportions)
local c = colsof(Proportions)
local p = 0
forvalues i = 1/`r' {
forvalues j = 1/`c' {
local p = `p' + Proportions[`i',`j']*ln(Proportions[`i',`j'])
}
}
local p = `p' + ln(`r'*`c')
di `p'
*-----------end example----------------
--- Steve Vaisey <[email protected]> wrote:
> Hello all,
>
> I am trying to implement the following formula for estimating the
> (standardized) informational entropy of a RxC contingency table:
> sum(p*ln(p))+ln(M) where p (subscript ij omitted) is the proportion of
> cases in each cell and M is the total number of cells. So far, I've
> only managed to accomplish the following:
>
> tab var1 var2, matcell(Cell)
> matrix Proportions = Cell/r(N)
-----------------------------------------
between 1/2/2006 and 31/3/2006 I will be
visiting the UCLA, during this time the
best way to reach me is by email
Maarten L. Buis
Department of Social Research Methodology
Vrije Universiteit Amsterdam
Boelelaan 1081
1081 HV Amsterdam
The Netherlands
visiting adress:
Buitenveldertselaan 3 (Metropolitan), room Z214
+31 20 5986715
http://home.fsw.vu.nl/m.buis/
-----------------------------------------
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