Hi without toy example it is rather complicated to check your function. So only few remarks:
Instead of generating 1 random number inside a loop generate whole vector of random numbers outside a loop and choose a number Do not mix ifelse with if. ifelse is intended to work with whole vector. Work with matrices instead of data frames whenever possible if speed is an issue. If I understand correctly you want to put 1 or 0 into one column based on: previous value in the same column comparison of some random number with predefined probabilities in vector of 6 values So here is vectorised version of your 4 ifs based on assumption 0 in col1 0 in col 2 = 5 0 in col1 1 in col 2 = 9 1 in col1 0 in col 2 = 6 1 in col1 1 in col 2 =10 col1<-sample(1:2, 20, replace=T) col2<-sample(c(4,8), 20, replace=T) col1+col2 [1] 5 6 9 6 6 5 9 10 9 9 6 9 10 6 10 9 10 9 5 5 cols<-as.numeric(as.factor(col1+col2)) cols [1] 1 2 3 2 2 1 3 4 3 3 2 3 4 2 4 3 4 3 1 1 And here is computed comparison of six values p (ortho obs used) with 20 generated random values ran<-runif(20) p<-runif(8) comparison <- outer(ran,p, "<") [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [1,] FALSE TRUE FALSE TRUE TRUE TRUE TRUE TRUE [2,] FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE [3,] FALSE TRUE FALSE TRUE FALSE TRUE TRUE FALSE [4,] FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE [5,] FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE [6,] FALSE TRUE FALSE TRUE FALSE TRUE FALSE FALSE [7,] FALSE TRUE FALSE TRUE FALSE TRUE FALSE FALSE [8,] FALSE TRUE FALSE TRUE TRUE TRUE TRUE TRUE [9,] FALSE TRUE FALSE TRUE TRUE TRUE TRUE TRUE [10,] FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE [11,] FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE [12,] FALSE TRUE FALSE TRUE TRUE TRUE TRUE TRUE [13,] FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE [14,] FALSE TRUE FALSE TRUE TRUE TRUE TRUE TRUE [15,] TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE [16,] FALSE TRUE FALSE TRUE TRUE TRUE TRUE TRUE [17,] FALSE TRUE FALSE TRUE FALSE TRUE FALSE FALSE [18,] FALSE TRUE FALSE TRUE TRUE TRUE TRUE TRUE [19,] FALSE TRUE FALSE TRUE TRUE TRUE TRUE TRUE [20,] FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE Now the only what you need to put in loop is to select appropriate column from matrix comparison based on value on cols vector and 0 or 1 in previous row of station column. Something like (untested) gen.log<-rep(NA, nrow(genmat)-1) for (i in 2:nrow(genmat)) { gen.log[i] <- if( genmat[i-1, num] ==0) comparison[i, cols[i]] else comparison[i,cols[i+5]] } genmat[2:nrow(genmat), num] <- gen.log*1 Regards Petr r-help-boun...@r-project.org napsal dne 11.08.2010 18:35:37: > Hello Everyone! > > Here's what I'm trying to do. I'm working on generating occurrences of > precipitation based upon precipitation occurrence for a station during the > previous day and two stations that have already been generated by joint > probablities and 1st order Markov chains or by the same generation process. > This has to be done for each remaining stations for each month. > > > genmat # 7 stations in this example, line_before is the climatology of the > last day of the previous month. Stations 4 and 6 have been generated already > in this example > [,1] [,2] [,3] [,4] [,5] [,6] [,7] > line_before 1 1 1 0 1 1 1 > NA NA NA 1 NA 0 NA > NA NA NA 0 NA 0 NA > NA NA NA 0 NA 0 NA > NA NA NA 0 NA 0 NA > NA NA NA 0 NA 0 NA > NA NA NA 0 NA 0 NA > NA NA NA 0 NA 0 NA > NA NA NA 1 NA 0 NA > NA NA NA 1 NA 1 NA > NA NA NA 1 NA 1 NA > NA NA NA 0 NA 0 NA > NA NA NA 0 NA 0 NA > NA NA NA 1 NA 1 NA > NA NA NA 0 NA 0 NA > NA NA NA 0 NA 0 NA > NA NA NA 0 NA 0 NA > NA NA NA 0 NA 0 NA > NA NA NA 0 NA 0 NA > NA NA NA 1 NA 1 NA > NA NA NA 0 NA 0 NA > NA NA NA 1 NA 1 NA > NA NA NA 1 NA 1 NA > NA NA NA 1 NA 1 NA > NA NA NA 0 NA 0 NA > NA NA NA 0 NA 1 NA > NA NA NA 0 NA 0 NA > NA NA NA 0 NA 0 NA > NA NA NA 1 NA 1 NA > NA NA NA 1 NA 1 NA > NA NA NA 1 NA 1 NA > NA NA NA 0 NA 0 NA > > num # station to generate > [1] 2 > > use1 # 1st station to use in generation > [1] 6 > > use2 # 2nd station to use in generation > [1] 4 > > > genmat = event.gen2(genmat,use1,use2,num,ortho_obs_used) # Generation > function shown below > > genmat # genmat - after it has gone through station 2 > [,1] [,2] [,3] [,4] [,5] [,6] [,7] > line_before 1 1 1 0 1 1 1 > NA 0 NA 1 NA 0 NA > NA 0 NA 0 NA 0 NA > NA 0 NA 0 NA 0 NA > NA 0 NA 0 NA 0 NA > NA 0 NA 0 NA 0 NA > NA 0 NA 0 NA 0 NA > NA 0 NA 0 NA 0 NA > NA 0 NA 1 NA 0 NA > NA 1 NA 1 NA 1 NA > NA 1 NA 1 NA 1 NA > NA 1 NA 0 NA 0 NA > NA 0 NA 0 NA 0 NA > NA 1 NA 1 NA 1 NA > NA 0 NA 0 NA 0 NA > NA 0 NA 0 NA 0 NA > NA 0 NA 0 NA 0 NA > NA 0 NA 0 NA 0 NA > NA 0 NA 0 NA 0 NA > NA 1 NA 1 NA 1 NA > NA 0 NA 0 NA 0 NA > NA 1 NA 1 NA 1 NA > NA 0 NA 1 NA 1 NA > NA 1 NA 1 NA 1 NA > NA 0 NA 0 NA 0 NA > NA 1 NA 0 NA 1 NA > NA 0 NA 0 NA 0 NA > NA 0 NA 0 NA 0 NA > NA 1 NA 1 NA 1 NA > NA 1 NA 1 NA 1 NA > NA 1 NA 1 NA 1 NA > NA 0 NA 0 NA 0 NA > > Where event.gen2 is this function: > > event.gen2 = function(genmat,use1,use2,num,ortho_obs_used){ > > for(r in 2:nrow(genmat)){ > > ran = runif(1,0,1) > > if(genmat[r,use1]==0 & genmat[r,use2]==0){ > genmat[r,num]<-ifelse(genmat[r-1,num]==0,ifelse(ran<ortho_obs_used$Pr[1],1, > 0),ifelse(ran<ortho_obs_used$Pr[4],1,0)) > } > > if(genmat[r,use1]==0 & genmat[r,use2]==1){ > genmat[r,num]<-ifelse(genmat[r-1,num]==0,ifelse(ran<ortho_obs_used$Pr[2],1, > 0),ifelse(ran<ortho_obs_used$Pr[5],1,0)) > } > > if(genmat[r,use1]==1 & genmat[r,use2]==0){ > genmat[r,num]<-ifelse(genmat[r-1,num]==0,ifelse(ran<ortho_obs_used$Pr[3],1, > 0),ifelse(ran<ortho_obs_used$Pr[7],1,0)) > } > > if(genmat[r,use1]==1 & genmat[r,use2]==1){ > genmat[r,num]<-ifelse(genmat[r-1,num]==0,ifelse(ran<ortho_obs_used$Pr[6],1, > 0),ifelse(ran<ortho_obs_used$Pr[8],1,0)) > } > > gc() > } > > genmat > > } > > #### > > ortho_obs_used is a data frame that contains the probablity of precipitation > occurring on a given day for a specific set of condtions. > For instance ortho_obs_used$Pr[1] is the probablity of rain at station s for > day d, given that there was no rain at station s for day d-1 and no rain at > either of the other two stations for day d. > > The event.gen2 function handles the generation, and it runs quickly for the > 5 remaining stations and one month, but I have to run this for 317 stations > over 48 months or more, and it becomes a really bad bottleneck. So what I'd > like to know is if there is anyway that I can re-write this function to work > without a loop. I couldn't find anything from previous posts about getting > out of loops where the previous iteration is required to determine the next > calculation. > > Sorry for the length of the post, but I thought it best to try to explain > what I was doing first, before diving into my question > > Thanks in advance! > > Adrienne Wootten > Graduate Research Assistant/Environmental Meteorologist > M.S. Atmospheric Science > NC State University > State Climate Office of North Carolina > Raleigh, NC 27695 > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.