1. Assume that the probability of rain tomorrow is 0.5 if it is raining today, and assume that the probability of its being clear (no rain) tomorrow is 0.9 if it is clear today. Also assume that these probabilities do not change if information is also provided about the weather before today. (a) Formulate the evolution of the weather as a Markov chain by defining its states and giving its (one-step) transition matrix. (b) Find the n-step transition matrix P(n) for n = 2, 5, 10, 20. (c) The probability that it will rain today is 0.4. Use the results from part (b) to determine the probability that it will rain n days from now, for n = 2, 5, 10, 20.

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1. Assume that the probability of rain tomorrow is 0.5 if it is raining today, and assume that the probability of its
being clear (no rain) tomorrow is 0.9 if it is clear today. Also assume that these probabilities do not change if
information is also provided about the weather before today.
(a) Formulate the evolution of the weather as a Markov chain by defining its states and giving its (one-step)
transition matrix.
(b) Find the n-step transition matrix P(n) for n = = 2, 5, 10, 20.
(c) The probability that it will rain today is 0.4. Use the results from part (b) to determine the probability that it
will rain n days from now, for n = 2, 5, 10, 20.
Transcribed Image Text:1. Assume that the probability of rain tomorrow is 0.5 if it is raining today, and assume that the probability of its being clear (no rain) tomorrow is 0.9 if it is clear today. Also assume that these probabilities do not change if information is also provided about the weather before today. (a) Formulate the evolution of the weather as a Markov chain by defining its states and giving its (one-step) transition matrix. (b) Find the n-step transition matrix P(n) for n = = 2, 5, 10, 20. (c) The probability that it will rain today is 0.4. Use the results from part (b) to determine the probability that it will rain n days from now, for n = 2, 5, 10, 20.
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