| edm_nearest | R Documentation | 
edm_nearest calculates the shortest euclidean distance found for
every point of one matrix among those of a second. In other words, if
m1, m2 have n rows, the result will be the shortest distance
for the first point of m1 to any point of m2 and so on,
n times. This function is used internally but may be of interest for
other analyses.
edm_nearest(m1, m2, full = FALSE)
| m1 | The first  | 
| m2 | The second  | 
| full | 
 | 
So far this function is quite time consumming since it performs  n
\times n  euclidean distance computation.  If one wishes to align two (or
more shapes) Procrustes surimposition may provide a better solution.
If full is TRUE, returns a list with two
components: d which is for every point of m1 the shortest
distance found between it and any point in m2, and pos the
(m2) row indices of these points. Otherwise returns d as a
numeric vector of the shortest distances.
ed, edm, dist.
x <- matrix(1:10, nc=2)
edm_nearest(x, x+rnorm(10))
edm_nearest(x, x+rnorm(10), full=TRUE)
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