Stratified sampling technique
The stratified sampling technique is a well-established area in statistical sampling (Cochran, 1966). Variance reduction by the stratified sampling technique is achieved by taking more samples in important subregions. Consider a problem in which the expectation of a function g (X) is sought, where X is a random variable with a PDF fx(x), x є E. Referring to Fig. 6.13, the domain E for the random variable X is divided into M disjoint subregions Em, m = 1, 2,…, M. That is,
m
S = U Sm 0 = Sm Fl Sm! m = m
m=1
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Let pm be the probability that random variable X will fall within the subregion Em, that is, f fx(x)dx = pm. Therefore, it is true that Lmpm = 1.
The expectation of g (X) can be computed as
m.. M
G = g(x) fx(x) dx =^2 / g(x) fx(x) dx =^2 Gm (6.86)
m=1J Em m=1
where Gm = fw g...
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