Hi, Gabor, got it. Thanks a lot. I have one more question about how the "predict" function works here, especially for the lag(Y,-1) part.
In my model, I assume I know predictors x and z in the next two years, and use them to predict Y. For each forecast step at time t, the lag(Y,-1) in the model should be the estimated result from the last forecast step. For example, the prediction of the Y in 2007 should be based on the estimated Y for 2006, not the actual number already in my dataset. Before I report my results, I want to make sure the "predict" function works in this way. Thanks. Harry On Thu, Jul 23, 2009 at 10:28 AM, Gabor Grothendieck < [email protected]> wrote: > Please provide your code in a reproducible form (as requested previously). > > Here we fit with first 9 points and then add a point for prediction. (Of > course your model can only predict the current value of Y so you may > have to rethink your model even aside from the implementation if you > really want to predict future values of Y.) > > > library(dyn) > > set.seed(123) > > tt <- ts(cbind(Y = 1:10, x = rnorm(10), z = rnorm(10))) > > L <- function(x, k = 1) lag(x, -k) > > tt.zoo <- as.zoo(tt) > > fit <- dyn$lm(Y ~ L(Y) + L(x, 0:2) + z, tt.zoo[-10, ]) > > predict(fit, tt.zoo) > 1 2 3 4 5 6 7 8 9 10 11 12 > NA NA 3 4 5 6 7 8 9 10 NA NA > > > > > On Thu, Jul 23, 2009 at 1:01 PM, Hongwei Dong<[email protected]> wrote: > > Hi, Gabor and Other R users, > > I'm re-posting my script and the results I got. > > > > here is the dynamic model I used to estimate in-sample model > (1996-2006) > > and it works: > > > > fit<-dyn$lm(Y~lag(Y,-1)+z+x+lag(x,-1)+lag(x,-2)+lag(x,-3)+lag(x,-4)) > > Then I used this model to do out sample forecast with the following > > scripts, which do not work: > > > > z<-ts(Z[41:52],start=2006,frequency=4) > > x<-ts(X[41:52],start=2006,frequency=4) > > newdata<-data.frame(cbind(z,x)) > > newdata<-ts(newdata,start=2006,frequency=4) > > pred<-predict(fit,newdata) > > Here is the results I got from R: > > Qtr1 Qtr2 Qtr3 Qtr4 > > 2006 NA NA NA NA > > 2007 3083.362 NA NA NA > > 2008 NA NA NA NA > > 2009 NA NA NA NA > > > > I got only one prediction for the first quarter in 2007. Intuitively, > there > > might be two problems: the definition of the newdata and how to define Y > in > > newdata. But I just can't figure this out. It will greatly appreciated if > > someone can give me some help. Thanks. > > Harry > > > > > > On Thu, Jul 23, 2009 at 5:15 AM, Gabor Grothendieck > > <[email protected]> wrote: > >> > >> You have to use consistent classes. You can't start out using > >> ts class and then suddenly switch to zoo class as if you had been > >> using zoo all along. Either use ts everywhere or zoo everywhere. > >> > >> Also in the future please post reproducible examples as requested > >> at the bottom of every message to r-help. That means include > >> a minimal amount of data so we can get exactly what you > >> are getting. > >> > >> On Thu, Jul 23, 2009 at 4:48 AM, Hongwei Dong<[email protected]> wrote: > >> > Thanks, Gabor. This is really helpful. > >> > When the regressive part, lag(Y,-1), is not included, my sytax works > >> > well. > >> > However, when I include the lag(Y) in the model, the prediction part > >> > does > >> > not work. Here is my sytax for in-sample estimation and it works well: > >> > fit<-dyn$lm(Y~lag(Y,-1)+x+lag(x,-1)+lag(x,-2)+lag(x,-3)+lag(x,-4)+z). > >> > Then I use this model to do out of sample prediction: > >> > x<-ts(X[41:52],start=2006,frequency=4) > >> > z<-ts(Z[41:52],start=2006,frequency=4) > >> > newdata<-data.frame(cbind(x,z)) > >> > newdata<-zooreg(newdata) > >> > pred<-predict(fit,newdata) > >> > With these, I got weird result, a prediction for each year from year 1 > >> > to > >> > the first quarter of year 2007 (all "NA"). What I expect is a > prediction > >> > for > >> > the 8 quarters from 2007 to 2008. Intuitively, I know there must be > >> > something wrong with my newdata definition. But I can't figure it out. > >> > I'll > >> > appreciate it very much if you can give some suggestions to modify my > >> > syntax. Thanks. > >> > > >> > Harry > >> > > >> > > >> > > >> > > >> > > >> > > >> > > >> > > >> > > >> > > >> > > >> > On Wed, Jul 22, 2009 at 10:53 PM, Gabor Grothendieck > >> > <[email protected]> wrote: > >> >> > >> >> Here is an example closer to yours. > >> >> > >> >> > library(dyn) > >> >> > set.seed(123) > >> >> > x <- zooreg(rnorm(10)) > >> >> > y <- zooreg(rnorm(10)) > >> >> > L <- function(x, k = 1) lag(x, k = -k) > >> >> > mod <- dyn$lm(y ~ L(y) + L(x, 0:2)) > >> >> > mod > >> >> > >> >> Call: > >> >> lm(formula = dyn(y ~ L(y) + L(x, 0:2))) > >> >> > >> >> Coefficients: > >> >> (Intercept) L(y) L(x, 0:2)1 L(x, 0:2)2 L(x, 0:2)3 > >> >> 0.06355 -0.74540 0.63649 0.44957 -0.41360 > >> >> > >> >> > newdata <- cbind(x = c(coredata(x), rnorm(1)), y = c(coredata(y), > >> >> > rnorm(1))) > >> >> > newdata <- zooreg(newdata) > >> >> > predict(mod, newdata) > >> >> 1 2 3 4 5 6 > >> >> 7 > >> >> NA NA 0.9157808 0.6056333 -0.5496422 1.5984615 > >> >> -0.2574875 > >> >> 8 9 10 11 12 13 > >> >> -1.6148859 0.3329285 -0.5284646 -0.1799693 NA NA > >> >> > >> >> > >> >> On Thu, Jul 23, 2009 at 1:04 AM, Gabor > >> >> Grothendieck<[email protected]> wrote: > >> >> > Use dyn.predict like this: > >> >> > > >> >> >> library(dyn) > >> >> >> x <- y <- zoo(1:5) > >> >> >> mod <- dyn$lm(y ~ lag(x, -1)) > >> >> >> predict(mod, list(x = zoo(6:10, 6:10))) > >> >> > 7 8 9 10 > >> >> > 7 8 9 10 > >> >> > > >> >> > > >> >> > On Thu, Jul 23, 2009 at 12:54 AM, Hongwei Dong<[email protected]> > >> >> > wrote: > >> >> >> I have a dynamic time series model like this: > >> >> >> dyn$lm( y ~ lag(y,-1) + x + lag(x,-1)+lag(x,-2) ) > >> >> >> > >> >> >> I need to do an out of sample forecast with this model. Is there > any > >> >> >> way I > >> >> >> can do this with R? > >> >> >> It would be greatly appreciated if some one can give me an > example. > >> >> >> Thanks. > >> >> >> > >> >> >> > >> >> >> Harry > >> >> >> > >> >> >> [[alternative HTML version deleted]] > >> >> >> > >> >> >> ______________________________________________ > >> >> >> [email protected] mailing list > >> >> >> https://stat.ethz.ch/mailman/listinfo/r-help > >> >> >> PLEASE do read the posting guide > >> >> >> http://www.R-project.org/posting-guide.html > >> >> >> and provide commented, minimal, self-contained, reproducible code. > >> >> >> > >> >> > > >> > > >> > > > > > > [[alternative HTML version deleted]] ______________________________________________ [email protected] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
