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Introduction to Probability MSIS 575 Homework 4 Instructor: Farid Alizadeh Due Date: Saturday December 16, 2000 in class last updated on December 14, 2000 1. Consider the following chain (If sum of probabilities out of a state does not add up to 1 assume a loop over that state with probability equal to the slack): 3 6 A AK A A1 1 2/3 A1 A 1/3 A A A AA U ? / 2 1 4 - 5 @ 6 I 3/5 1 1 1/5 @ @ @ 0 (a) Which classes are transient and which are persistent? (b) Find the period of each state. (c) What are the equivalence classes under the “communicate” relationship? Which group of classes are closed? (d) Starting from 0, what is the probability of hitting 6? (e) Starting from 1, what is the probability of hitting 3? What is the average number of steps to to hit 3? (f) Starting from 1, what is the long-term proportion of time spent in each of states 2, 3 and 1? 2. A fair die with six sides, marked by numbers 1 through 6, is thrown repeatedly. At the kth toss we are in state j if j is the largest number that has occurred so far. 1 MSIS 565, Fall 2000 Homework 4 Due date: 12/16/00 (a) What is the transition probability matrix of this chain? (b) Which states are persistent and which are transient? (c) What is the stationary distribution of this matrix? 3. During period n Zn+1 people enter a line for service in a bank (the period is a fixed amount of time, say 30 seconds.) And on period n + 1 exactly one person is served. Therefore denoting by Xn the number of people waiting in line at period n we have, Xn+1 = (Xn + 1)+ + Zn+1 where a+ = max(0, a). The random variables Zn are i.i.d with common distribution pk = Pr[Z1 = k]. (a) Show that {Xn }n≥0 is a Markov chain with transition probability p0 p1 p2 p3 · · · p0 p1 p2 p3 · · · 0 p0 p1 p2 · · · 0 p0 p1 · · · .. .. .. .. . . . . (b) Optional bonus question: Let q = (q0 , q1 , q2 , . . . ) be the stationary distribution of the system. Remember that qT P = qT . If the Generating function P(z) = p0 + p1 z + · · · is known, find the generating function Q(z) = q0 + q1 z + · · · . (c) Optional bonus question: If Zn each have Poisson distribution of rate λ (that is the number of people entering the line at each period follows the Poisson distribution), find the stationary distribution of the chain. 4. If X is N(µ, σ), show that Pr[|X − µ| < 0.675σ] = 0.5. 5. If U is uniform on [0,1] what is the density √function of distribution function, mean, and variance of U. √ U? Also find 6. If U is uniform in [-1,1] what is density function of U2 ? Also find distribution function, mean, and variance of U2 . 7. Find the density function of eZ if Z is N(µ, σ). Find Distribution, mean and variance o eZ . (This distribution is called the lognormal distribution since its logarithm is normal.) 8. Note: You may wish to start working on this question after Mondays’s lecture. The joint density function of Random variables X and Y is given by 2 −λy λ e , 0 ≤ x ≤ y, λ > 0 f(x, y) = 0 elsewhere 2 MSIS 565, Fall 2000 Homework 4 Due date: 12/16/00 (a) Find the marginal density fX (x). (b) Find the marginal density fY (y). (c) Find the conditional density fX|Y (x|y). Also find E[X|Y = 2]. (d) Find the conditional density fY|X (y|x). Also find E[Y|X = 3]. 9. canceled Show that if X is Fn,m then X−1 is Fm,n . 10. canceled Show that if T is tn then T 2 is F1,n . 11. canceled If X and Y are independent exponential random variables with λ = 1, then X/Y has F distribution. Also find degrees of freedom m and n. 3