I've got quite a large dataset I want to analyse with dmn. Running it with
fit <- mclapply(1:20, dmn, count=count, verbose=TRUE)
on my desktop did not complete within 30 days (using all 4 cores). Probably power outage cancelled calculations as the system was reloaded. I divided the dataset into parts and run it also on a server. Some parts were finished but there is a 7-days limit and some needed more time. I would prefer to run the data as a full dataset.
Can I replace
fit <- mclapply(1:20, dmn, count=count, verbose=TRUE)
with
fit1 <- mclapply(1:7, dmn, count=count, verbose=TRUE)
fit2 <- mclapply(8:14, dmn, count=count, verbose=TRUE)
fit3 <- mclapply(15:20, dmn, count=count, verbose=TRUE)
How to combine fit1 (1:7), fit2 (8:14), and fit3 (15:20) into fit (1:20) ?
I've got quite a large dataset I want to analyse with
dmn. Running it withfit <- mclapply(1:20, dmn, count=count, verbose=TRUE)on my desktop did not complete within 30 days (using all 4 cores). Probably power outage cancelled calculations as the system was reloaded. I divided the dataset into parts and run it also on a server. Some parts were finished but there is a 7-days limit and some needed more time. I would prefer to run the data as a full dataset.
Can I replace
fit <- mclapply(1:20, dmn, count=count, verbose=TRUE)with
How to combine
fit1(1:7),fit2(8:14), andfit3(15:20) intofit(1:20) ?