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1楼 2015-09-08 00:43:27

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LHSDESIGN Generate a latin hypercube sample.
X=LHSDESIGN(N,P) generates a latin hypercube sample X containing N
values on each of P variables.  For each column, the N values are
randomly distributed with one from each interval (0,1/N), (1/N,2/N),
..., (1-1/N,1), and they are randomly permuted.

X=LHSDESIGN(...,'PARAM1',val1,'PARAM2',val2,...) specifies parameter
name/value pairs to control the sample generation.  Valid parameters
are the following:

   Parameter Value
   'smooth'    'on' (the default) to produce points as above, or
                  'off' to produces points at the midpoints of
                  the above intervals:  .5/N, 1.5/N, ..., 1-.5/N.
   'iterations' The maximum number of iterations to perform in an
                  attempt to improve the design (default=5)
   'criterion'  The criterion to use to measure design improvement,
                  chosen from 'maximin' (the default) to maximize the
                  minimum distance between points, 'correlation' to
                  reduce correlation, or 'none' to do no iteration.

Latin hypercube designs are useful when you need a sample that is
random but that is guaranteed to be relatively uniformly distributed
over each dimension.

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2楼2017-07-26 09:50:50

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2楼: Originally posted by 培根加油条 at 2017-07-26 09:50:50
LHSDESIGN Generate a latin hypercube sample.
X=LHSDESIGN(N,P) generates a latin hypercube sample X containing N
values on each of P variables. For each column, the N values are
random ...

http://cn.mathworks.com/matlabce ... ions/2/download/zip

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