I study a problem of a random walk with drift and an absorbing boundary. The system is well theoretically understood. My task is to simulate it numerically, in particular to generate random numbers from this distribution, see the formula. It is the distribution of the coordinate x at time t given the starting point x_0, the noise intensity \sigma and the drift \mu. The question is how to generate random numbers from this distribution? I can of course use the inverse transform sampling, but it is slow. May be I can make use of the fact that the probability density function is the difference of two Gaussian functions? Can I relate somehow my distribution with the normal distribution?
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You want to generate `x` and `t` at `x0` (i.e. using p(x,t|x0))? Or you need to generate `x` given `t` and `x0`? – Severin Pappadeux May 14 '19 at 20:46
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I need to generate x given t and x_0. Sorry, the notations are not clear indeed. – Vladimir Klinshov May 15 '19 at 10:28
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What programming language are you using? – Peter O. Jul 11 '20 at 16:12