Two time series questions: FITTING TRANSFER FUNCTIONS WITH LAGS: Consider the following toy example: > dates <- paste(11:21, "/01/2005", sep="") > Dates <- as.Date(dates, "%d/%m/%Y") > set.seed(1) > DF <- data.frame(date=Dates, y=rnorm(11), x=rnorm(11, 3)) > arima(DF$y, c(1,0,0), xreg=lag(DF$x, 1)) ar1 intercept lag(DF$x, 1) -0.3876 -1.1328 0.4280 s.e. 0.3556 0.6417 0.1945 sigma^2 estimated as 0.3807: log likelihood = -10.38, aic = 28.76 > arima(DF$y, c(1,0,0), xreg=lag(DF$x, 2)) ar1 intercept lag(DF$x, 2) -0.3876 -1.1328 0.4280 s.e. 0.3556 0.6417 0.1945 sigma^2 estimated as 0.3807: log likelihood = -10.38, aic = 28.76 ****I NAIVELY THOUGHT THAT "lag" WOULD DO SOMETHING HERE. Evidently, it didn't. ****The following seems to work: > arima(DF$y, c(1,0,0), xreg=c(DF$x[-1], NA)) ar1 intercept c(DF$x[-1], NA) -0.3943 -0.2155 0.1185 s.e. 0.3454 0.8024 0.2464 sigma^2 estimated as 0.4889: log likelihood = -10.7, aic = 29.39 > arima(DF$y, c(1,0,0), xreg=c(DF$x[-(1:2)], NA, NA)) ar1 intercept c(DF$x[-(1:2)], NA, NA) -0.2385 -0.6430 0.2472 s.e. 0.3073 0.8592 0.2485 sigma^2 estimated as 0.491: log likelihood = -9.6, aic = 27.2 Is there a better way? ASSOCIATING A CALENDAR DATE WITH A 'ts' OBJECT In the previous example, I'd like to convert x and y into "ts" objects, retaining "Dates". Is there a way to do this? The following did not work: > ts(DF$y, start=Dates[1]) Error in Math.difftime((end - start) * frequency + 1.01) : floor not defined for difftime objects Thanks, spencer graves