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What are the examples of stochastic processes with continuous random variables and discrete time? Also, is Brownian motion defined on $t = [0,\infty[$?

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Three types of examples among many possibilities:

(1) Random walks (on the line, plane, etc.) with a uniformly distributed displacement left or right at each discrete step in time. The location at a given step is a continuous random variable.

(2) Many Gibbs samplers are discrete-time ergodic Markov chains with continuous values generated at each step. The chain is contrived so that the limiting distribution of the chain is the posterior distribution of a Bayesian model. By simulating the chain and looking at many simulated values near the end of a run, one can approximate the unknown posterior distribution. (One simple example here.)

(3) Metropolis-Hastings approximations usually involve random walks in multi-dimensional spaces. At each step a random displacement in the space is made and a candidate value (often continuous) is generated, the candidate value can be accepted or rejected according to some criterion. If rejected, the old value is replicated and a new displacement is tried. The result is a simulated sample from a multivariate distribution. (Wikipedia discussion.)

BruceET
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