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Implicit Sampling, with Application to Data Assimilation
[chapter]
2014
Partial Differential Equations: Theory, Control and Approximation
There are many computational tasks in which it is necessary to sample a given probability density (pdf), i.e., use a computer to construct a sequence of independent random vectors x i , i = 1, 2, . . . , whose histogram converges to the given pdf. This can be difficult because the sample space can be huge, and more important, because the portion of the space where the density is significant can be very small, so that one may miss it by an ill-designed sampling scheme. Indeed, Markov-chain Monte
doi:10.1007/978-3-642-41401-5_6
fatcat:b5wtscblfjaebpryde4emaaesq