(a) Find valid initiation and update functions for the Markov chain in Example 2.2 (the Los Angeles weather), with starting distribution (0) = (½, ½). (b) Write a computer program for simulating the Markov chain, using the initiation and update functions in (a). (c) For n ≥ 1, define Y, to be the proportion of rainy days up to time n, i.e., Yn = n 1 n+1 I(X=s1)⋅ i=0 Simulate the Markov chain for (say) 1000 steps, and plot how Yn evolves with time. What seems to happen to Yn when n gets large?

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Chapter2: Second-order Linear Odes
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C)

(a) Find valid initiation and update functions for the Markov chain in Example 2.2
(the Los Angeles weather), with starting distribution (0) = (½, ½).
(b) Write a computer program for simulating the Markov chain, using the initiation
and update functions in (a).
(c) For n ≥ 1, define Y, to be the proportion of rainy days up to time n, i.e.,
Yn
=
n
1
n+1
I(X=s1)⋅
i=0
Simulate the Markov chain for (say) 1000 steps, and plot how Yn evolves
with time. What seems to happen to Yn when n gets large?
Transcribed Image Text:(a) Find valid initiation and update functions for the Markov chain in Example 2.2 (the Los Angeles weather), with starting distribution (0) = (½, ½). (b) Write a computer program for simulating the Markov chain, using the initiation and update functions in (a). (c) For n ≥ 1, define Y, to be the proportion of rainy days up to time n, i.e., Yn = n 1 n+1 I(X=s1)⋅ i=0 Simulate the Markov chain for (say) 1000 steps, and plot how Yn evolves with time. What seems to happen to Yn when n gets large?
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