Determine whether a vector is in the closure of the convex hull of some sample of vectors
is.inCH
returns TRUE
if and only if p
is contained in
the convex hull of the points given as the rows of M
. If p
is
a matrix, each row is tested individually, and TRUE
is returned if
all rows are in the convex hull.
is.inCH(p, M, verbose = FALSE, ...)
p |
A d-dimensional vector or a matrix with d columns |
M |
An r by d matrix. Each row of |
verbose |
A logical vector indicating whether to print progress |
... |
arguments passed directly to linear program solver |
The d-vector p
is in the convex hull of the d-vectors
forming the rows of M
if and only if there exists no separating
hyperplane between p
and the rows of M
. This condition may be
reworded as follows:
Letting q=(1 p')' and L = (1 M), if the maximum value of
z'q for all z such that z'L ≤ 0 equals zero (the maximum
must be at least zero since z=0 gives zero), then there is no separating
hyperplane and so p
is contained in the convex hull of the rows of
M
. So the question of interest becomes a constrained optimization
problem.
Solving this problem relies on the package lpSolve
to solve a linear
program. We may put the program in "standard form" by writing z=a-b,
where a and b are nonnegative vectors. If we write x=(a'
b')', we obtain the linear program given by:
Minimize (-q' q')x subject to x'(L -L) ≤ 0 and x ≥ 0. One additional constraint arises because whenever any strictly negative value of (-q' q')x may be achieved, doubling x arbitrarily many times makes this value arbitrarily large in the negative direction, so no minimizer exists. Therefore, we add the constraint (q' -q')x ≤ 1.
This function is used in the "stepping" algorithm of Hummel et al (2012).
Logical, telling whether p
is (or all rows of p
are)
in the closed convex hull of the points in M
.
Hummel, R. M., Hunter, D. R., and Handcock, M. S. (2012), Improving Simulation-Based Algorithms for Fitting ERGMs, Journal of Computational and Graphical Statistics, 21: 920-939.
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