Question

In: Statistics and Probability

Suppose that whether or not it rains today depends on previous weather conditions through the last...

Suppose that whether or not it rains today depends on previous weather conditions through the last two days.
Specifically, suppose that if it has rained for the past two days, then it will rain tomorrow with probability 0.7; if it rained
today but not yesterday, then it will rain tomorrow with probability 0.5; if it rained yesterday but not today, then it will
rain tomorrow with probability 0.4; if it has not rained in the past two days, then it will
rain tomorrow with probability 0.2. If we let the state at time n depend only on whether or not it is raining at time n,
Q1. ---whether the preceding model is a Markov chain or not? And why? .
And we can transform this model into a Markov chain by saying that the state at any time is determined by the weather
conditions during both that day and the previous day. In other words, we can say that the process is in
state0 if it rained both today and yesterday,
state1 if it rained today but not yesterday,
state2 if it rained yesterday but not today,
state3 if it did not rain either yesterday or today.
Q2.---The preceding would then represent a four-state Markov chain having a transition probability matrix
P, and find P, plz?
Q3. ---Given that it rained on Monday and Tuesday, what is the probability that it will rain on Thursday?

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