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Q: Can a Markov chain in general have an infinite number of states? O yes no Previous
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Consider the following Markov chain. Assuming that the process starts in state 4, what is the
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- A Markov Chain has the transition matrix r-[% *]. P = and currently has state vector % % ]: What is the probability it will be in state 1 after two more stages (observations) of the process? (A) % (B) 0 (C) /2 (D) 24 (E) 12 (F) ¼ (G) 1 (H) 2247Determine whether the Markov chain with matrix of transition probabilities P is absorbing. Explain.
- Consider a Markov chain in the set {1, 2, 3} with transition probabilities p12 = p23 = p31 = p, p13 = p32 = p21 = q = 1 − p, where 0 < p < 1. Determine whether the Markov chain is reversible.Problem: Construct an example of a Markov chain that has a finite number of states and is not recurrent. Is your example that of a transient chain?5. Explain what is meant by BLUE estimates and the Gauss-Markov theorem. Mathematics relevant proofs will be rewarded. [:
- an 15 A continuous-time Markov chain (CTMC) has three states (1, 2, 3). ed dout of The average time the process stays in states 1, 2, and 3 are 3, 11.9, and 3.5 seconds, respectively. question The steady-state probability that this CTMC is in the second state ( , ) isFind the limiting distribution for this Markov chain. Then give an interpretation of what the first entry of the distribution you found tells you based on the definition of a limiting distribution. Your answer should be written for a non-mathematician and should consist of between 1 and 3 complete sentences without mathematical symbols or terminology.Consider the Markov chain with three states,S={1,2,3}, that has the following transition matrix 1.Draw the state transition diagram for this chain. (10 marks)
- Which of the following best describes the long-run probabilities of a Markov chain {Xn: n = 0, 1, 2, ...}? O the probabilities of eventually returning to a state having previously been in that state O the fraction of time the states are repeated on the next step O the fraction of the time being in the various states in the long run O the probabilities of starting in the various states • Previous Not saved SimpfunPlease do question 45
