ps = scramble(p,
type
)
ps = scramble(p,'clear')
ps = scramble(p)
ps = scramble(p,
returns
a scrambled copy type
)ps
of the point set p
of
the qrandset
class,
created using the scramble type specified in the string type
.
Point sets from different subclasses of qrandset
support
different scramble types, as indicated in the following table.
Subclass  Scramble Types 

haltonset 

sobolset 

ps = scramble(p,'clear')
removes all scramble
settings from p
and returns the result in ps
.
ps = scramble(p)
removes all scramble settings
from p
and then adds them back in the order they
were originally applied. This typically results in a different point
set because of the randomness of the scrambling algorithms.
Use haltonset
to generate
a 3D Halton point set, skip the first 1000 values, and then retain
every 101st point:
p = haltonset(3,'Skip',1e3,'Leap',1e2) p = Halton point set in 3 dimensions (8.918019e+013 points) Properties: Skip : 1000 Leap : 100 ScrambleMethod : none
Use scramble
to apply reverseradix scrambling:
p = scramble(p,'RR2') p = Halton point set in 3 dimensions (8.918019e+013 points) Properties: Skip : 1000 Leap : 100 ScrambleMethod : RR2
Use net
to
generate the first four points:
X0 = net(p,4) X0 = 0.0928 0.6950 0.0029 0.6958 0.2958 0.8269 0.3013 0.6497 0.4141 0.9087 0.7883 0.2166
Use parenthesis indexing to generate every third point, up to the 11th point:
X = p(1:3:11,:) X = 0.0928 0.6950 0.0029 0.9087 0.7883 0.2166 0.3843 0.9840 0.9878 0.6831 0.7357 0.7923
[1] Kocis, L., and W. J. Whiten. "Computational Investigations of LowDiscrepancy Sequences." ACM Transactions on Mathematical Software. Vol. 23, No. 2, 1997, pp. 266–294.
[2] Matousek, J. "On the L2Discrepancy for Anchored Boxes." Journal of Complexity. Vol. 14, No. 4, 1998, pp. 527–556.