The transition matrix P for a Markov chain with states 0 and 1 is given. Assume that the chain starts in state 0 at time n = 0. Find the probability that the chain will be in state 1 at time n. 14 P= 34 15 n=3 The probability that the chain will be in state 1 at time n-3 is (Simplify your answer.)
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- Explain how you can determine the steady state matrix X of an absorbing Markov chain by inspection.Consider the Markov chain whose matrix of transition probabilities P is given in Example 7b. Show that the steady state matrix X depends on the initial state matrix X0 by finding X for each X0. X0=[0.250.250.250.25] b X0=[0.250.250.400.10] Example 7 Finding Steady State Matrices of Absorbing Markov Chains Find the steady state matrix X of each absorbing Markov chain with matrix of transition probabilities P. b.P=[0.500.200.210.300.100.400.200.11]12. Robots have been programmed to traverse the maze shown in Figure 3.28 and at each junction randomly choose which way to go. Figure 3.28 (a) Construct the transition matrix for the Markov chain that models this situation. (b) Suppose we start with 15 robots at each junction. Find the steady state distribution of robots. (Assume that it takes each robot the same amount of time to travel between two adjacent junctions.)