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Discrete-time markov chain (continuation)
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CHAPMAN-KOLMOGOROV EQUATIONS IN MATRIX FORM
Starting from the transition matrix π, we have π (π) =ππ= π π π (π) =π π (π) = π π π (π) =π π (π) = π π In general, π (π) =π π (πβπ) = π π
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CHAPMAN-KOLMOGOROV EQUATIONS IN MATRIX FORM
Recall our example with π= π π.π π π.π π.π π π.π π π.π π π.π π π π.ππ π π.ππ Refer to the MS Excel file.
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Unconditional state probabilities
If we start with πΏ π =π, what are the probabilities π· πΏ ππ =π , π· πΏ ππ =π , π· πΏ ππ =π and π·{ πΏ ππ =π}? After 10 time periods
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Unconditional state probabilities
After 10 matrix multiplications: π (ππ) β π.ππ π.ππ π.ππ π.ππ π.ππ π.ππ π.ππ π.ππ π.ππ π.ππ π.ππ π.ππ π.ππ π.ππ π.ππ π.ππ
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Unconditional state probabilities
If we start with πΏ π =π, what are the probabilities π· πΏ ππ =π , π· πΏ ππ =π , π· πΏ ππ =π and π·{ πΏ ππ =π}? π π π π π.ππ π.ππ π.ππ π.ππ π.ππ π.ππ π.ππ π.ππ π.ππ π.ππ π.ππ π.ππ π.ππ π.ππ π.ππ π.ππ
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Unconditional state probabilities
If we start with πΏ π =π, the probabilities are π· πΏ ππ =π =π.ππ, π· πΏ ππ =π =π.ππ, π· πΏ ππ =π =π.ππ and π· πΏ ππ =π =π.ππ.
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STEADY-STATE PROBABILITIES
After 50 matrix multiplications: π (ππ) β π.ππ π.ππ π.ππ π.ππ π.ππ π.ππ π.ππ π.ππ π.ππ π.ππ π.ππ π.ππ π.ππ π.ππ π.ππ π.ππ What is the meaning of this?
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STEADY-STATE PROBABILITIES
π ππ (ππ) βπ.ππ π ππ (ππ) βπ.ππ π ππ (ππ) βπ.ππ π ππ (ππ) βπ.ππ This is called the steady-state probabilities of the Markov Chain.
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STEADY-STATE PROBABILITIES
π ππ (ππ) βπ.ππ π ππ (ππ) βπ.ππ π ππ (ππ) βπ.ππ π ππ (ππ) βπ.ππ Note: Do not be confused with steady-state probabilities and stationary transition probabilities.
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STEADY-STATE PROBABILITIES
π ππ (ππ) βπ.ππ π ππ (ππ) βπ.ππ π ππ (ππ) βπ.ππ π ππ (ππ) βπ.ππ Can we derive them directly without doing too many matrix multiplications?
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STEADY-STATE PROBABILITIES
In some cases, we can use the concept of fixed- point iteration. π=ππ The steady-state probabilities: π= π π π π π π β¦ π π΄ .
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STEADY-STATE PROBABILITIES
Recall again our example: π π π π π π π π = π π π π π π π π π π.π π π.π π.π π π.π π π.π π π.π π π π.ππ π π.ππ We also include in our equations: π π + π π +π π + π π =π
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STEADY-STATE PROBABILITIES
Solving it will result in: π π βπ.ππππ π π βπ.ππππ π π βπ.π π π βπ.πππ
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