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Stochastic Processes

Stochastic Processes Practice 1

Problems on Poisson processes, Markov chains, Brownian motion, martingales, and queueing theory

8 Problems
Suggested: 2 hours

Instructions

  • • Try to solve each problem before viewing the solution
  • • Click "Show Solution" to reveal the answer and detailed explanation
  • • Focus on understanding the problem-solving methodology
1Poisson Process: Waiting Times
Problem

Customers arrive at a service counter according to a Poisson process with rate λ = 3 per hour.

(1) What is the probability that exactly 5 customers arrive in the next 2 hours?

(2) Given that 5 customers arrived in 2 hours, what is the probability that exactly 2 arrived in the first hour?

(3) What is the expected waiting time until the 4th customer arrives?

2Discrete-Time Markov Chain: Long-Run Behavior
Problem

A Markov chain has state space {1, 2, 3} with transition matrix:

P=(0.50.30.20.20.50.30.10.40.5)P = \begin{pmatrix} 0.5 & 0.3 & 0.2 \\ 0.2 & 0.5 & 0.3 \\ 0.1 & 0.4 & 0.5 \end{pmatrix}

(1) Find the stationary distribution π.

(2) If X₀ = 1, what is P(X₂ = 3)?

(3) Is this chain irreducible? Is it aperiodic?

3Birth-Death Process
Problem

Consider a birth-death process with birth rates λₙ = nλ and death rates μₙ = nμ for n ≥ 1, μ₀ = 0.

(1) Write the generator matrix Q for states {0, 1, 2} when λ = 2, μ = 1.

(2) Find the stationary distribution if it exists.

(3) What is the physical interpretation of this process?

4Random Walk
Problem

A symmetric random walk on integers starts at X₀ = 0. At each step, the walk moves +1 or -1 with equal probability.

(1) Find P(X₄ = 0).

(2) Find E[X₁₀].

(3) What is the probability that the walk first returns to 0 at time n = 4?

5Brownian Motion: Properties
Problem

Let {B(t), t ≥ 0} be a standard Brownian motion.

(1) Find P(B(2) > 1 | B(1) = 0.5).

(2) Calculate Cov(B(2), B(5)).

(3) What is the distribution of M = max{B(t): 0 ≤ t ≤ 1}?

6Martingales
Problem

Let {Xₙ, n ≥ 0} be a sequence of i.i.d. random variables with E[Xᵢ] = 0 and Var(Xᵢ) = σ².

Define Sₙ = X₁ + X₂ + ... + Xₙ with S₀ = 0.

(1) Show that {Sₙ} is a martingale.

(2) Show that {Sₙ² - nσ²} is a martingale.

(3) Use the optional stopping theorem to find E[Sₜ] where T is a stopping time with E[T] < ∞.

7Renewal Process
Problem

A machine breaks down, and the time until breakdown follows an Exponential(λ) distribution. After each breakdown, repair takes a random time with Exponential(μ) distribution, independent of breakdown times.

(1) What is the long-run proportion of time the machine is operating?

(2) If λ = 0.5 failures/hour and μ = 2 repairs/hour, find the expected number of failures in 100 hours.

8Queueing Theory: M/M/1 Queue
Problem

Consider an M/M/1 queue with arrival rate λ = 4 customers/hour and service rate μ = 5 customers/hour.

(1) Find the utilization ρ and verify stability.

(2) Find the average number of customers in the system L.

(3) Find the average time a customer spends in the system W.

(4) What is the probability that an arriving customer finds the system empty?

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