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Jun 09'24

Exercise

[math] \newcommand{\NA}{{\rm NA}} \newcommand{\mat}[1]{{\bf#1}} \newcommand{\exref}[1]{\ref{##1}} \newcommand{\secstoprocess}{\all} \newcommand{\NA}{{\rm NA}} \newcommand{\mathds}{\mathbb}[/math]

In his book, Wahrscheinlichkeitsrechnung und Statistik,[Notes 1] A. Engle proposes an algorithm for finding the fixed vector for an ergodic Markov chain when the transition probabilities are rational numbers. Here is his algorithm: For each state [math]i[/math], let [math]a_i[/math] be the least common multiple of the denominators of the non-zero entries in the [math]i[/math]th row. Engle describes his algorithm in terms of moving chips around on the states---indeed, for small examples, he recommends implementing the algorithm this way. Start by putting [math]a_i[/math] chips on state [math]i[/math] for all [math]i[/math]. Then, at each state, redistribute the [math]a_i[/math] chips, sending [math]a_ip_{ij}[/math] to state [math]j[/math]. The number of chips at state [math]i[/math] after this redistribution need not be a multiple of [math]a_i[/math]. For each state [math]i[/math], add just enough chips to bring the number of chips at state [math]i[/math] up to a multiple of [math]a_i[/math]. Then redistribute the chips in the same manner. This process will eventually reach a point where the number of chips at each state, after the redistribution, is the same as before redistribution. At this point, we have found a fixed vector. Here is an example:

[math]1[/math] [math]2[/math][math]3[/math]
[math]\mat{P}=\,\,[/math] [math]\begin{array}{c c c c} 1 \\ 2\\ 3 \end{array}[/math] [math]\begin{pmatrix} 1 & 2 & 3 \\ 1/2 & 1/4 & 1/4 \\ 1/2 & 0 & 1/2 \\ 1/2 & 1/4 & 1/4\\ \end{pmatrix};[/math]


We start with [math]\mat {a} = (4,2,4)[/math]. The chips after successive redistributions are shown in Table.

[math] \begin{array}{lll} (4 & 2\;\; & 4)\\ (5 & 2 & 3)\\ (8 & 2 & 4)\\ (7 & 3 & 4)\\ (8 & 4 & 4)\\ (8 & 3 & 5)\\ (8 & 4 & 8)\\ (10 & 4 & 6)\\ (12 & 4 & 8)\\ (12 & 5 & 7)\\ (12 & 6 & 8)\\ (13 & 5 & 8)\\ (16 & 6 & 8)\\ (15 & 6 & 9)\\ (16 & 6 & 12)\\ (17 & 7 & 10)\\ (20 & 8 & 12)\\ (20 & 8 & 12)\ . \end{array} [/math]

We find that [math]\mat {a} = (20,8,12)[/math] is a fixed vector.

  • Write a computer program to implement this algorithm.
  • Prove that the algorithm will stop. Hint: Let [math]\mat{b}[/math] be a vector with integer components that is a fixed vector for [math]\mat{P}[/math] and such that each coordinate of the starting vector [math]\mat{a}[/math] is less than or equal to the corresponding component of [math]\mat{b}[/math]. Show that, in the iteration, the components of the vectors are always increasing, and always less than or equal to the corresponding component of [math]\mat{b}[/math].

Notes

  1. A. Engle, Wahrscheinlichkeitsrechnung und Statistik, vol. 2 (Stuttgart: Klett Verlag, 1976).