search for: flightfact

df is a very large data frame with arrival estimates for many flights (DF$flightfact) at random times (df$PredTime). The error of the estimate is df$dt. My problem is that I want to know the prediction error at each minute before landing. This code works, but is very slow, and dominates everything. I tried using split(), but that rapidly ate up my 12 GB of memory. So, is there a be...

...t;T") #Plot individual flight data dfm = df dfm = dfm[!df$MsgType=="AS",] # Eliminate AS messages dfm$MsgType=drop.levels(dfm$MsgType) dfm = dfm[as.numeric(dfm$PredTime) < 60.0,] dfm$tc= as.factor(floor(dfm$PredTime/10.0)) # get 10-minute bin dfm$flightfact = drop.levels(dfm$flightfact) row.names(dfm) = seq(1:dim(dfm)[1]) #Find max and min error for each flight library(zoo) maxes = tapply(dfm$dt,dfm$flightfact,FUN=max) # Returns a list mins = tapply(dfm$dt,dfm$flightfact,FUN=min) mdf = data.frame(flight=index(maxes), maxes...