Li
> Sent: Friday, September 24, 2010 3:44 AM
> To: r-help@r-project.org
> Subject: [R] boundary check
>
> Dear R,
>
> I have a covariates matrix with 10 observations, e.g.
>
> > X <- matrix(rnorm(50), 10, 5)
> > X
> [,1][,2]
Feng
thanks for this. The problem you report is
reproducible; it originates from simplex()
of the boot packge.
It is ultimately due to
the fact that x_i is precisely *on* the convex hull,
which is evidently causing problems. I'll
investigate it.
In the short term, you can break the degeneracy:
Hi,
Below Baptiste's message I attach the R code and the .Rd documentation I
treated as 'final', it may be slightly different from that in the Dec 2009
post.
I did submit if for inclusion in the geometry package, but last time I
checked it wasn't there.
I have found (and others have reported
Thanks. I agree with you that the speed and memory issues might be
(actually is) a big problem for big dimensions. It is interesting to
know to solve this by using linear programming. Buy the way, it seems
a potential bug in your function if you try this
> X <- matrix(rnorm(50), 10, 5)
> x_i<-X[1
Hi,
I remember a discussion we had on this list a few months ago for a
better way to decide if a point is inside a convex hull. It eventually
lead to a R function in this post,
http://tolstoy.newcastle.edu.au/R/e8/help/09/12/8784.html
I don't know if it was included in the geometry package in th
Hello,
If an N-dimensional convex hull fits your idea of a "smallest ball"
then you could try the convhulln function in the geometry package.
For testing if a new point is inside a previously derived hull, one
brute force approach is to rbind the new point to your data, generate
a new hull and se
Hello
convex hulls in large numbers of dimensions are hard.
For your problem, though, one can tell whether a given
point is inside or outside by using linear programming:
> X <- matrix(rnorm(50), 10, 5)
> x_i <- matrix(rnorm(5), 1, 5)
> isin.chull
function(candidate,p,plot=FALSE,give.answers=FA
Dear R,
I have a covariates matrix with 10 observations, e.g.
> X <- matrix(rnorm(50), 10, 5)
> X
[,1][,2][,3][,4] [,5]
[1,] 0.24857135 0.30880745 -1.44118657 1.10229027 1.0526010
[2,] 1.24316806 0.36275370 -0.40096866 -0.24387888 -1.5324384
[3
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