Dear Fellows: Thanks you all for your great help. Without your  
guidance I'd not have been able to get this far. So this is the  
current problem: I have a series (dataframe with 1 column and 283  
rows, all with numbers (no NA's) that go from 0 to 3 or 4 with up to  
14 decimals. They indicate a percentage. I have to apply a formula to  
that dataframe that uses 4 variables I have already stored in a  
dataframe called combmatrix.

df.clases = sapply(seq(1,by=1,length=3921225),function(x)  
((AlicuotaBruta/llmcc$Clase)*combmatrix[1,x]+((1/llmcc 
$Categoria)*AlicuotaBruta)*combmatrix[2,x]+(AlicuotaBruta*llmcc 
$Phi)*combmatrix[3,x]+ (AlicuotaBruta*llmcc$Rf)*combmatrix[4,x]))

The number 3921225 corresponds to the number of dimensions of the  
combmatrix created with the combd function using 4 elements per  
dimension oscilating from 0.01 to 100.
FIRST PROBLEM: How can I re-proportion the results of each iteration  
so df.classes sums 100 or 1 before testing the results?
SECOND PROBLEM: Since I cannot save df.classes (its too big for my  
computer), I would need to test and know which value of x hold the  
correct combination for the desired results and save it phsically in  
my disk, is that possible with sapply o mapply?.

The desired results are so that, among the 283 values resulting from  
each iteration I need to know how big each element of a certain group  
of 12 are. In other words, I have selected a test group in the  
original dataframe and, in order to know if the formula results are  
better, I need to compare each new group among itself so, for example,  
if element 1 is bigger than element 2 for more than 40% I will have to  
discard it, and the same thing happens if element 2 different for less  
than 20% of the value of element 1. The same rules apply for the rest  
of the 12 elements, although the boundaries are different.
Any ideas on how could I implement this.


Sonríe... mañana será peor. Filosofía de Murphy.
------------------------------
Jesús Guillermo Andrade (Abg.)
Gerente de Litigios y Corporativo. EDM. AC. API.
Andrade & Moreno S.C. (http://amlegal.wordpress.com/)


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