Classification of states of continuous-time chains
[13/92%]Let for all and let for all . All other transition rates are .
Solve the steady-state equations and show that for all .
Find the transition probabilities for the embedded Markov chain and show that the chain is null recurrent.
For any state , consider the renewal process for which the Markov process starts in state and renewals occur on each transition to state . Show that, for each , the expected inter-renewal interval is equal to .
Show that the expected number of transitions between each entry into state is infinite. Explain why this does not mean that an infinite number of transitions can occur in a finite time.
Hint for (c): Use renewal-reward theory.
Let be a Markov chain on with generator given by
Show that is recurrent. Is positive recurrent?
Let be a Markov chain on with generator satisfying
Show that is transient, but has an invariant distribution. Explain.
Let be a continuous-time Markov chain with generator . Show that is irreducible if and only if for any pair of distinct states there exists a sequence of distinct states such that .
Let be a continuous-time Markov chain with transition probabilities and define where is the time of the first jump of . Show that, if , then if and only if is recurrent.
Let be the simple symmetric random walk on the integers in continuous time, so that
Show that the walk is recurrent. Let be the time spent visiting during an excursion from 0. Find the distribution of .
Let be a transient state of a continuous-time Markov chain with . Show that the total time spent in state has an exponential distribution.
Let be an asymmetric simple random walk in continuous time on the non-negative integers with retention at , so that
Suppose that and . Show that the total time spent in state is exponentially distributed with parameter .
Assume now that has some general distribution with probability generating function . Find the expected amount of time spent at 0 in terms of .
Let where is a Markov chain and . Show that is recurrent for if and only if it is recurrent for . Show that is irreducible if and only if is irreducible.
Prove that, for the embedded Markov chain , the states and communicate if and only if for all .
Let a jump Markov process with values 1, 2, 3, 4, and 5 be defined by the transition intensity matrix
Find the transition probability matrix and classify the states.
A homogeneous jump Markov process with values 1, 2, 3, 4, 5, and 6 is given by the transition intensity matrix
Find the transition probability matrix of the embedded Markov chain and use it to classify the states and find the absorption probabilities for each of the essential state classes.
Find all stationary distributions for the Markov process and for the embedded Markov chain. Do they coincide? Why?
A homogeneous jump Markov process with values 1, 2, 3, 4, 5, and 6 is given by the transition intensity matrix
Find the transition probability matrix of the embedded Markov chain . Use it to classify the states and find the absorption probabilities for each of the essential classes.
Find all stationary distributions of the process and of the embedded Markov chain . Do they coincide? Why?
Find the limiting distributions for the Markov process and for the Markov chain, if .
Find the limiting distributions for the Markov process and for the Markov chain, if .