If poly were to be changed to allow NA's, how should it act in the
multivariate case when raw=FALSE?
Suppose x1 had an NA in position 1 only and x2 had NA in position 2 only.
Should the output matrix have NAs in all columns of rows 1 and 2 with its
coefs attribute reflectiing only the data in na.omit(cbind(x1,x2))? This
would make the output matrix orthonormal after NA removal.
Or should it remove NAs from the input vectors independently? This is
analogous to what predict.poly() currently does - different columns of the
output will have different patterns of NAs.
An example of the first method would be:
> poly(c(NA,2,5,7,8), c(1,NA,3,4,9), degree=2)
1.0 2.0 0.1 1.1 0.2
[1,] NA NA NA NA NA
[2,] NA NA NA NA NA
[3,] -0.7715167 0.2672612 -0.5132649 0.39599247 0.6350006
[4,] 0.1543033 -0.8017837 -0.2932942 -0.04525628 -0.7620008
[5,] 0.6172134 0.5345225 0.8065591 0.49781910 0.1270001
attr(,"degree")
[1] 1 2 1 2 2
attr(,"coefs")
[[1]]
[[1]]$alpha
[1] 6.666667 6.190476
[[1]]$norm2
[1] 1.000000 3.000000 4.666667 2.571429
[[2]]
[[2]]$alpha
[1] 5.333333 6.989247
[[2]]$norm2
[1] 1.00000 3.00000 20.66667 14.51613
attr(,"class")
[1] "poly" "matrix"
and the second
> poly(c(NA,2,5,7,8), c(1,NA,3,4,9), degree=2)
1.0 2.0 0.1 1.1 0.2
[1,] NA NA -0.55132280 NA 0.6398330
[2,] -0.7637626 0.3988620 NA NA NA
[3,] -0.1091089 -0.7407437 -0.21204723 0.02313625 -0.3442756
[4,] 0.3273268 -0.1709409 -0.04240945 -0.01388175 -0.6106021
[5,] 0.5455447 0.5128226 0.80577948 0.43958875 0.3150447
attr(,"degree")
[1] 1 2 1 2 2
attr(,"coefs")
[[1]]
[[1]]$alpha
[1] 5.500000 4.357143
[[1]]$norm2
[1] 1.00000 4.00000 21.00000 56.57143
[[2]]
[[2]]$alpha
[1] 4.250000 6.289568
[[2]]$norm2
[1] 1.0000 4.0000 34.7500 176.6331
attr(,"class")
[1] "poly" "matrix"
Bill Dunlap
TIBCO Software
wdunlap tibco.com
On Thu, Mar 24, 2016 at 4:54 AM, Martin Maechler <maech...@stat.math.ethz.ch
> wrote:
> >>>>> William Dunlap via R-help <r-help@r-project.org>
> >>>>> on Wed, 23 Mar 2016 13:56:35 -0700 writes:
>
> > I don't know what is in R's poly(), but if it is like S+'s or TERR's
> then
> > one could do
>
> > if (anyNA(x)) {
> > nax <- na.exclude(x)
> > px <- poly(x = nax, degree = degree, coefs = coefs, raw =
> > raw, simple = simple)
> > px <- structure(naresid(attr(nax, "na.action"), px), coefs
> > = attr(px, "coefs"), degree = attr(px, "degree"), class = attr(px,
> "class"))
> > return(px)
> > }
>
> > and get nice results in the usual raw=FALSE case as well. Similar
> stuff
> > could be done in the multivariate cases.
>
> I don't have too much time for that now,
> and I know that Bill Dunlap cannot provide patches for R --- for
> good reasons, though it's a pity for us! ---
> but you can, Liviu!
> So, and as you see at every startup of R :
>
> "R is a collaborative project with many contributors."
>
> I'm willing to try "good-looking" patches.
> (to the *sources*, *NOT* to a printout of the function in your R console!)
>
> Martin Maechler
> ETH Zurich and R Core Team.
>
> > Bill Dunlap
> > TIBCO Software
> > wdunlap tibco.com
>
> > On Wed, Mar 23, 2016 at 1:41 PM, Liviu Andronic <
> landronim...@gmail.com>
> > wrote:
>
> >> On Wed, Mar 23, 2016 at 9:29 PM, William Dunlap <wdun...@tibco.com>
> wrote:
> >> > I think the worst aspect of this restriction in poly() is that
> when
> >> > you use poly in the formula of a model-fitting function you cannot
> >> > have any missing values in the data, even if you supply
> >> > na.action=na.exclude.
> >> >
> >> > > d <- transform(data.frame(y=c(-1,1:10)), x=log(y))
> >> > Warning message:
> >> > In log(y) : NaNs produced
> >> > > fit <- lm(y ~ poly(x, 3), data=d, na.action=na.exclude)
> >> > Error in poly(x, 3) : missing values are not allowed in 'poly'
> >> >
> >> > Thus people are pushed to using a less stable formulation like
> >> > > fit <- lm(y ~ x + I(x^2) + I(x^3), data=d,
> na.action=na.exclude)
> >> >
> >> My difficulty precisely. What's more, I inspected the code for
> `poly`
> >> and at least for the simple case of raw=TRUE it seems trivial to
> >> support NAs. It suffices to change line 15 of the function:
> >> if (anyNA(x)) stop("missing values are not allowed in 'poly'")
> >>
> >> to:
> >> if (!raw && anyNA(x)) stop("missing values are not allowed in
> 'poly'")
> >>
> >> This way for raw polynomials estimation continues unimpeded. With
> the
> >> change above, I get this:
> >> > poly(x, degree = 2, raw=TRUE)
> >> 1 2
> >> [1,] NA NA
> >> [2,] 1 1
> >> [3,] 2 4
> >> [4,] 3 9
> >> [5,] 4 16
> >> [6,] 5 25
> >> [7,] 6 36
> >> [8,] 7 49
> >> [9,] 8 64
> >> [10,] 9 81
> >> [11,] 10 100
> >> attr(,"degree")
> >> [1] 1 2
> >> attr(,"class")
> >> [1] "poly" "matrix"
> >>
> >>
> >> Regards,
> >> Liviu
> >>
> >>
> >> >
> >> > Bill Dunlap
> >> > TIBCO Software
> >> > wdunlap tibco.com
> >> >
> >> > On Wed, Mar 23, 2016 at 12:59 PM, Liviu Andronic <
> landronim...@gmail.com
> >> >
> >> > wrote:
> >> >>
> >> >> Dear all,
> >> >> I'm a bit surprised by this behavior in poly:
> >> >>
> >> >> x <- c(NA, 1:10)
> >> >> poly(x, degree = 2, raw=TRUE)
> >> >> ## Error in poly(x, degree = 2, raw = TRUE) :
> >> >> ## missing values are not allowed in 'poly'
> >> >> x^2
> >> >> ## [1] NA 1 4 9 16 25 36 49 64 81 100
> >> >>
> >> >> As you can see, poly() will fail if the vector contains NAs,
> whereas
> >> >> it is perfectly possible to obtain the square of the vector
> manually.
> >> >>
> >> >> Is there a reason for this limitation in poly?
> >> >>
> >> >> Regards,
> >> >> Liviu
> >> >>
> >> >>
> >> >> --
> >> >> Do you think you know what math is?
> >> >> http://www.ideasroadshow.com/issues/ian-stewart-2013-08-02
> >> >> Or what it means to be intelligent?
> >> >> http://www.ideasroadshow.com/issues/john-duncan-2013-08-30
> >> >> Think again:
> >> >> http://www.ideasroadshow.com/library
> >> >>
> >> >> ______________________________________________
> >> >> R-help@r-project.org mailing list -- To UNSUBSCRIBE and more,
> see
> >> >> 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.
> >> >
> >> >
> >>
> >>
> >>
> >> --
> >> Do you think you know what math is?
> >> http://www.ideasroadshow.com/issues/ian-stewart-2013-08-02
> >> Or what it means to be intelligent?
> >> http://www.ideasroadshow.com/issues/john-duncan-2013-08-30
> >> Think again:
> >> http://www.ideasroadshow.com/library
> >>
>
> > [[alternative HTML version deleted]]
>
> > ______________________________________________
> > R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
> > 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]]
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