Examples of Markov Chains - A Center-biased Random Walk

A Center-biased Random Walk

Consider a random walk on the number line where, at each step, the position (call it x) may change by +1 (to the right) or -1 (to the left) with probabilities:

(where c is a constant greater than 0)


For example if the constant, c, equals 1, the probabilities of a move to the left at positions x = -2,-1,0,1,2 are given by respectively. The random walk has a centering effect that weakens as c increases.

Since the probabilities depend only on the current position (value of x) and not on any prior positions, this biased random walk satisfies the definition of a Markov chain.

Read more about this topic:  Examples Of Markov Chains

Famous quotes containing the words random and/or walk:

    “It is a secret from nobody that the famous random event is most likely to arise from those parts of the world where the old adage “There is no alternative to victory” retains a high degree of plausibility.”
    —Hannah Arendt (1906–1975)

    “Harry Morgan: Walk around me. No, go ahead. Walk around me, clear around. Do ya find anything?
    Slim/Marie Brown: No, no Steve. There are no strings tied to you. Not yet.”
    —Jules Furthman (1888–1960)