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Problems 10/3 1. Ehrenfast’s diffusion model:
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Problems, cont. 2. Discrete uniform on {0,...,n}
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Problems, cont. 3. where k=0?
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Classification of states A state i for a Markov chain X k is called persistent if and transient otherwise. Let and. j is persistent iff f jj =1. Let
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Some results Theorem: (a)P ii (s)=1+F ii (s)P ii (s) (b)P ij (s)=F ij (s)P ij (s) for i ≠ j. Proof: As for the random walk case we deduce from the Markov property that Multiply both sides by s m, sum over m≥1 to get
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Some results, cont. Corollary: (a)State j is persistent if and then for all i. (b)State j is transient if and thenfor all i. Proof: SInce we see that But(by Abel’s thm)
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A final consequence If i is transient, then Why? Example: Branching process What states are persistent? Transient? State 0 is called absorbing, since once the process reaches 0, it never leaves again.
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Mean recurrence time Let T i = min{n>0: X n = i} and i = E(T i |X 0 =i). For a transient state i = ∞. For a persistent state We call a recurrent state positive persistent if i < ∞, null persistent otherwise. Example: Simple random walk positive recurrent = non-null persistent
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A model for radiation damage Initial damage from radiation can either heal or get worse until it is visible. 0 is a healthy organism (absorbing) 3 visible damage (absorbing) 1 initial damage 2 amplified damage
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Radiation damage, cont. Recovery probability 0 is probability of reaching 0 before 3. Last step must go Thus
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Communication Two states i and j communicate,, if for some m. i and j intercommunicate,, if and. Theorem: is an equivalence relation. What do we need to prove?
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Equivalence classes of states Theorem: If then (a)i is transient iff j is transient (b)i is persistent iff j is persistent Proof of (a): Since there are m,n with By Chapman-Kolmogorov so summing over r we get
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Closed and irreducible sets A set C of states is closed if p ij =0 for all i in C, j not in C C is irreducible if for all i,j in C. Theorem: S=T+C 1 +C 2 +... where T are all transient, and the C i are irreducible disjoint closed sets of persistent states Note: The C i are the equivalence classes for
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Example S={0,1,2,3,4,5} {0,1},{4,5} closed irreducible persistent {2,3} transient. Why?
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Long-term behavior Recall from the 0-1 process that When does this not depend on n? (a)p 01 = p 11 (b) (c)
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Stationary distribution Case (b) is the general one. Here is the idea: Recall that (n) = (0) P n. In order to get the same distribution for all n, we use (0) = where solves P = (1) = P = P 2 = P = ... P n =
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Snoqualmie Falls so or
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