Date: Thu, 4 Apr 1996 11:28:56 -0500 From: pgilbert@bank-banque-canada.ca (Paul Gilbert) To: R-testers@stat.math.ethz.ch Subject: R-alpha: tsp problem Message-Id: <96Apr4.112451est.29451@mailgate.bank-banque-canada.ca> Here is a simple example of the tsp problem I'm having: > x <- 1:100 > x <- cbind(x, .5*x+ rnorm(100), .3*x+ rnorm(100)) > y <- x[,1:2] + matrix(rnorm(200), 100,2) > b <- lsfit(x[1:90,],y[1:90,]) > y <- ts(y, start=c(1961,1), freq=12) > b <- lsfit(x[1:90,],y[1:90,]) Error: invalid time series parameters specified by putting browser() lines in lsfit (I sure would appreciate it if someone could tell me a better way to find where things are going wrong) I narrowed this down to > z <- y[1:90,] > storage.mode(z) <- "double" Error: invalid time series parameters specified Also > tsp(y) [1] 1961.00 1969.25 12.00 Splus returns NULL (as per the "Blue Book" non-time series) for > tsp(y[1:90,]) [1] 1 90 1 and for > tsp(1:10) [1] 1 10 1 I think NULL would be safer. It is of course possible to do something better, but this is only one example of the many ways tsp is deficient. I think it would be best to just use the "Blue Book" tsp and do something else better. (I'm not the only one thinking of a complete re-write of time representation. I believe both the Federal Reserve Board in the States, and StatSci, also have plans.) Paul =-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=- r-testers mailing list -- To (un)subscribe, send subscribe or unsubscribe (in the "body", not the subject !) To: r-testers-request@stat.math.ethz.ch =-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-