28. Suppose that whether it rains in Charlotte tomorrow depends on the weather conditions for today and yesterday. Climate data from 2003 show that • If it rained yesterday and today, then it will rain tomorrow with probability 58. • If it rained yesterday but not today, then it will rain tomorrow with probability .29. If it rained today but not yesterday, then it will rain tomorrow with probability 47. • If it did not rain yesterday or today, then it will rain tomorrow with probability 31. Even though the weather depends on the last two days in this case, we can create a Markov chain model using the states 1 itrained yesterday and today 2 it rained yesterday but not today 3 it rained today but not yesterday 4 it did not rain yesterday or today So, for example, the probability of a transition from state I to state I is .58, and the transition from state I to state 3 is 0.

28. Suppose that whether it rains in Charlotte tomorrow depends on the weather conditions for today and yesterday. Climate data from 2003 show that • If it rained yesterday and today, then it will rain tomorrow with probability 58. • If it rained yesterday but not today, then it will rain tomorrow with probability .29. If it rained today but not yesterday, then it will rain tomorrow with probability 47. • If it did not rain yesterday or today, then it will rain tomorrow with probability 31. Even though the weather depends on the last two days in this case, we can create a Markov chain model using the states 1 itrained yesterday and today 2 it rained yesterday but not today 3 it rained today but not yesterday 4 it did not rain yesterday or today So, for example, the probability of a transition from state I to state I is .58, and the transition from state I to state 3 is 0.

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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