search for: time03

...aster than 'by' function tsDaply <- function(...) { library(plyr) e1 <- new.env(parent = baseenv()) #create a new env res <- daply(X, "ID", buildTimeSeriesFromDataFrame, env = e1) return(get("xx", e1)) # return xx from env } ##replicate 100 times #Time03 <- replicate(100, # system.time(tsDaply(X, X$ID))[[1]]) #median(Time03) # result tsDaply(X, X$ID) Thanks in advance for any input, best regards, Den

I?m wondering which is the most efficient (time, than memory usage) way to obtain a multivariate time series object from a data frame (the easiest data structure to get data from a database trough RODBC). I have a starting point using timeSeries or xts library (these libraries can handle time zones), below you can find code to test. Merging parallelization (cbind) is something I?m thinking at