search for: volocc

...the first, so I am quite certain the difference in speed is down to the Zoo version used. My code runs a fairly simple function over a time series using the following call to process a year of 30s data (9 columns, about a million rows): vals <- rollapply(data=ts.data[,c(n.3.cols, o.3.cols,volocc.cols)] ,width=40 ,FUN=rolling.function.fn(n.cols=n.3.cols,o.cols=o.3.cols,vo.cols=volocc.cols) ,by.column=FALSE ,align='right') (The rolling.function.fn call returns a function that is initialized with the initial cal...