Two Properties of Markov Models The general equations of an n-state Markov model can be expressed in terms of matrices as MP = dP/dt where P is the column vector P = [P1 P2 ... Pn]T and M is the n´ transition matrix with the components The symbol λi,j signifies the exponential transition rate from state i to state j. This includes both failure rates and repair rates, and it allows for transitions in both directions between every pair of states. For each j, let Cj denote the jth column vector of M, excluding the diagonal term Mj,j. Hence Cj has dimension n-1. This vector represents the transition rates from state j to each of the other n-1 states. We also define (dPj/dt)+ as the rate of probability flow into state j. Proposition: At steady-state conditions the quantity (dPj/dt)+/(1-Pj) for any state j depends on the direction of Cj but is independent of the magnitude. Proof: Let m denote the (n-1)´(n-1) matrix formed by deleting the jth row and column from the full transition matrix M, and let p denote the column vector formed by deleting the jth element from full state vector P. Then the equations of state give Setting dp/dt = 0 for the steady-state condition and solving this equation for p gives Now, letting I denote the identity row vector I = [1 1 ... 1] of dimension n-1, the conservation equation can be written as 1 - Pj = Ip. Hence, multiplying both sides of the above equation by I and substituting from the conservation equation, we have We also note that for the steady-state condition (dPj/dt)+ is equal to the rate of probability flowing out of state j, which is simply Pj I Cj. Consequently we have The column vector Cj can be written as the product of a scalar magnitude and a unit vector Uj pointing in the direction of Cj. Making this substitution, the magnitude cancels out, and we are left with Hence the left hand quantity depends on the direction of Cj, but not on the magnitude, which was to be shown. Discussion: This proposition tells us that the steady-state "hazard rate" (the left hand quantity in the preceding equation) for any state j is independent of the overall rate of outflow from that state, but it does depend on how that outflow is distributed to the other states of the model. Proposition: If the only non-zero component of Cj is λj,k, then for steady-state conditions the quantity (dPj/dt)+/(1-Pj) is equal to the reciprocal of the mean time of transition from state k to state j. Proof: In this case IUj = 1, so the reciprocal of the hazard rate is which is a scalar equal to the sum of the numbers in the kth column of m−1. We wish to show that this equals the mean time of transition from state k to state j. To find an explicit expression for this mean time, it is most convenient to suppress the "return path" by setting λj,k = 0, and then begin with the initial condition Pk(0) = 1 and integrate the time from t = 0 to infinity, weighted according to dPj(t)/dt, which is the probability density function for entry into state j. Hence the mean time is given by Notice that setting λj,k equal to zero prior to solving for Pj(t) does not affect the time required for an object to transition from state k to state j, because this transition does not involve the return path from j back to k. Now, since we have suppressed the return path, the system equations are simply dp/dt = mp , which has the explicit dynamic solution Notice that, since our initial condition is Pk(0) = 1, and state k is the exclusive return state from state j, the vector p(0) equals the vector Uj defined previously. We also have the conservation equation Substituting into the mean time integral gives which was to be shown. Discussion: In retrospect the proof of this proposition is slightly superfluous, because it's essentially an immediate corollary of the previous proposition. Notice that the hazard rate of any state j is independent of the magnitude of the outflow rate from that state (by the previous proposition), so we can consider the limit as λj,k approaches infinity. In this limit the value of Pj approaches zero, so the hazard rate goes to (dPj/dt)+, which is just the flow rate into state j (which also equals the flow rate out of state j). Also, it is stipulated that all the flow from state j goes to state k, so each element of the steady-state flow proceeds from state k to state j (by some route) and then immediately jumps back to state k to begin again. The steady-state flow rate (dPj/dt)+ in the limit as λj,k approaches infinity is therefore the reciprocal of the mean time of transition from state k to state j. It follows from the previous proposition that, for any value of λj,k, the hazard rate (dPj/dt)+/(1−Pj) equals the reciprocal of the mean time to transition from state k to state j, which was to be shown. Return to MathPages Main Menu