it's not totally clear to me what exactly do you need in this case, but
have a look at the following:
Atr <- cbind(rep(1:0, each = 4), 1, c(1, rep(0, 7)), 1)
unSpells <- colSums(Atr == 0)
unSpells[unSpells == 0] <- 1
unSpells
I hope it helps.
Best,
Dimitris
Mario Lavezzi wrote:
Hello,
I have the following problem.
I am running simulations on possible states of a set of agents
(1=employed, 0=unemployed).
I store these simulated time series in a matrix like the following,
where rows indicates time periods, columns the number of agents (4
agents and 8 periods in this case):
Atr=[
1 1 1 1
1 1 0 1
1 1 0 1
1 1 0 1
0 1 0 1
0 1 0 1
0 1 0 1
0 1 0 1]
At this point, I need to update a vector ("unSpells") which contains the
lenghts of unemployment spells, and is initialized with ones.
Practically, in the case represented I need to store the value "4" at
position 1 of unSpells and "7" at position 3 of unSpells (that is, I
care only of those who, in the last row, are zeros).
I am doing this in the following way (tt+1 indicates the time period
reached by the simulation, n the number of agents):
unSpells = matrix(1,nrow=1,ncol=n) ppp=apply(Atr[1:(tt+1),],2,rle)
for(i in (1:n)[Atr[tt+1,]==0]){
unSpells[i]=tail(ppp[[i]]$lengths,1)
}
It works, but the for (i in ...) loop slows down the simulation a lot.
Any suggestion on how to avoid this loop? (or in general, to speed up
this part of the simulation)
Thanks!!
Mario
--
Dimitris Rizopoulos
Assistant Professor
Department of Biostatistics
Erasmus Medical Center
Address: PO Box 2040, 3000 CA Rotterdam, the Netherlands
Tel: +31/(0)10/7043478
Fax: +31/(0)10/7043014
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