R help - Nov 2009 - dynlm predict with newdata?

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On Sun, 22 Nov 2009, zubin wrote:
> Hello, can one use predict, as you can with other model objects like lm,
> with dynlm to predict a new data set that is identical in field names,
> just a different time period.
>
> Be nice if you could, I don't really want to create a new data set with
> all the lags, hoping it would generate dynamically.  Does not seem to
> work, get a # of column error.  Any suggestions?
Currently, this is not possible, yet. It would indeed be nice if dynlm() 
could figure out which of the variables are determined by the response and 
predict these recursively, while the remaining variables would need to be 
provided (or even updated by auxiliary AR models). But currently, it's not 
clear to me how all these cases should be resolved exactly and how the 
additional formula parsing should be done, so it's not implemented yet. 
Sorry...
Z

>
> R> str(dfz)
> An 'xts' object from 2009-09-25 09:45:06 to 2009-10-19 15:00:57
containing:
>  Data: num [1:28232, 1:8] 0.54771 -0.00825 1.27406 0.69705 1.08107 ...
> - attr(*, "dimnames")=List of 2
>  ..$ : NULL
>  ..$ : chr [1:8] "PC1" "PC2" "PC3"
"PC4" ...
>  Indexed by objects of class: [POSIXt,POSIXct] TZ: GMT
>  xts Attributes:
> NULL
>
> R> str(z)
> An 'xts' object from 2009-10-21 09:45:04 to 2009-10-21 15:00:56
containing:
>  Data: num [1:2304, 1:8] -0.5044 1.237 -0.7764 0.3931 0.0629 ...
> - attr(*, "dimnames")=List of 2
>  ..$ : NULL
>  ..$ : chr [1:8] "PC1" "PC2" "PC3"
"PC4" ...
>  Indexed by objects of class: [POSIXt,POSIXct] TZ: GMT
>  xts Attributes:
> NULL
>
>
> dols = dynlm(FAS0 ~ L(FAS0,1:10) + L(PC1,0:10) + L(PC2,0:10) +
> L(PC3,0:10) + L(PC4,0:10) + L(PC5,0:10) + L(PC6,0:10) + L(PC7,0:10),
> data=dfz)
>
> R> predict(dols,newdata=z)
>
> /*Error in fix.by(by.x, x) : 'by' must match numbers of columns*/
>
> 	[[alternative HTML version deleted]]
>
> ______________________________________________
> R-help at r-project.org 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.
>
>

The dyn package has a predict method that can typically be used to
predict one step ahead (and you can use a loop to get multiple steps).
 To use just preface lm (or glm or any model fitting function in R
that uses model.frame in the same way as lm).  It works with zoo,
zooreg, ts, its and irts class series.

library(dyn) # this also pulls in zoo

# generate test data
set.seed(123)
x <- zooreg(rep(1, 10))
for(i in 2:10) x[i] <- x[i-1] + rnorm(1)

# fit model
Lag <- function(x, k = 1) lag(x, -k)
mod <- dyn$lm(x ~ Lag(x))

# perform prediction and plot
x. <- predict(mod, list(x = x))
plot(cbind(x, x.), col = 1:2, screen = 1)

# get more info
package?dyn
?dyn

On Sun, Nov 22, 2009 at 9:43 PM, zubin <binabina at bellsouth.net>
wrote:
> Hello, can one use predict, as you can with other model objects like lm,
> with dynlm to predict a new data set that is identical in field names,
> just a different time period.
>
> Be nice if you could, I don't really want to create a new data set with
> all the lags, hoping it would generate dynamically. ?Does not seem to
> work, get a # of column error. ?Any suggestions?
>
>
> R> str(dfz)
> An 'xts' object from 2009-09-25 09:45:06 to 2009-10-19 15:00:57
containing:
> ?Data: num [1:28232, 1:8] 0.54771 -0.00825 1.27406 0.69705 1.08107 ...
> ?- attr(*, "dimnames")=List of 2
> ?..$ : NULL
> ?..$ : chr [1:8] "PC1" "PC2" "PC3"
"PC4" ...
> ?Indexed by objects of class: [POSIXt,POSIXct] TZ: GMT
> ?xts Attributes:
> ?NULL
>
> R> str(z)
> An 'xts' object from 2009-10-21 09:45:04 to 2009-10-21 15:00:56
containing:
> ?Data: num [1:2304, 1:8] -0.5044 1.237 -0.7764 0.3931 0.0629 ...
> ?- attr(*, "dimnames")=List of 2
> ?..$ : NULL
> ?..$ : chr [1:8] "PC1" "PC2" "PC3"
"PC4" ...
> ?Indexed by objects of class: [POSIXt,POSIXct] TZ: GMT
> ?xts Attributes:
> ?NULL
>
>
> dols = dynlm(FAS0 ~ L(FAS0,1:10) + L(PC1,0:10) + L(PC2,0:10) +
> L(PC3,0:10) + L(PC4,0:10) + L(PC5,0:10) + L(PC6,0:10) + L(PC7,0:10),
> data=dfz)
>
> R> predict(dols,newdata=z)
>
> /*Error in fix.by(by.x, x) : 'by' must match numbers of columns*/
>
> ? ? ? ?[[alternative HTML version deleted]]
>
> ______________________________________________
> R-help at r-project.org 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.
>