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generates random variates with multivariate Lipschitz density

RanLip generates random variates with an arbitrary multivariate Lipschitz density.

While generation of random numbers from a variety of distributions is implemented in many packages (like GSL library and UNURAN library, generation of random variate with an arbitrary distribution, especially in the multivariate case, is a very challenging task. RanLip is a method of generation of random variates with arbitrary Lipschitz-continuous densities, which works in the univariate and multivariate cases, if the dimension is not very large (say 3-10 variables).

Lipschitz condition implies that the rate of change of the function (in this case, probability density p(x)) is bounded:


From this condition, we can build an overestimate of the density, so called hat function h(x)>=p(x), using a number of values of p(x) at some points. The more values we use, the better is the hat function. The method of acceptance/rejection then works as follows: generatea random variate X with density h(x); generate an independent uniform on (0,1) random number Z; if p(X)<=Z h(X), then return X, otherwise repeat all the above steps.

RanLip constructs a piecewise constant hat function of the required density p(x) by subdividing the domain of p (an n-dimensional rectangle) into many smaller rectangles, and computes the upper bound on p(x) within each of these rectangles, and uses this upper bound as the value of the hat function.

Package version:1.0-4.1

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