Stochastic processes with independent increments, Wiener process and Poisson process. Non-homogeneous and compound Poisson processes. Discrete time Markov chains (classification of states, ergodic properties), random walks, branching processes. Continuous-time Markov processes, Kolmogorov's differential equations. Birth and death processes, applications to Markov queueing models. Non-Markov processes, renewal process, renewal reward process, alternating and regenerative processes, ergodic theorems. Semi-Markov processes. Applications in reliability and inventory models. Selected topics from stationary processes and time-series.
İlk dosyayı sen ekleyebilirsin — notlar, geçmiş finaller, çözümler, cheat-sheet, ne varsa. Drive linki / PDF / ZIP / fotoğraf, hepsi olur.
Şu an: mail at, ben düzenleyip yayına alayım. Form/upload UX yakında geliyor (Kimya tasarlıyor).
| Dönem | Course CPA | |
|---|---|---|
| 2023-2024 Spring | 3.14 | 1 sec · 9 öğr |
| 2022-2023 Spring | 3.57 | 1 sec · 3 öğr |
| 2021-2022 Spring | 3.28 | 1 sec · 6 öğr |
| 2020-2021 Spring | 2.60 | 1 sec · 5 öğr |
| 2019-2020 Spring | 3.07 | 1 sec · 10 öğr |
| 2018-2019 Spring | 3.27 | 1 sec · 8 öğr |
| 2017-2018 Spring | 2.33 | 1 sec · 8 öğr |
| 2015-2016 Spring | 2.81 | 1 sec · 14 öğr |
| 2014-2015 Spring | 3.13 | 1 sec · 8 öğr |
| 2013-2014 Spring | 3.01 | 1 sec · 7 öğr |
Aggregate course GPA — Bilkent STARS'tan public data. Hoca-bazlı per-section detayı için STARS evaluation report →. Öğrenci anket cevapları KVKK kapsamında defter'de tutulmaz.
Course Learning Outcomes: Course Learning Outcome Assessment
Review of probability concepts Transformations, intro to stochastic processes Introduction to Poisson process interarrival, waiting times. Counting process, Poisson process. Exponential distribution. Non-homogeneous and compound Poisson processes. Intro to renewal processes. Some limit theorems Wald's equation, Asymptotic behavior of the number of renewals. Regenerative process. Alternating process. Limiting probabilities. Applications. Delayed Renewal Process, Equilibrium RP, Renewal Reward Processes(RRP). Markov Chains(MC), Chapman Kolmogorov Equations Ergodic MC, limits theorems. Transition among classes. Introduction to Continuous-time Markov chains. Embedded Markov chain. Kolmogorov's differential equations. Birth and Death Processes. Limiting probabilities for Birth and Death processes. Long-run cost functionals. Approximations and uniformization. Some queueing models. Semi-Markov Processes. ECTS - Workload Table: Activities Number Hours Workload Homework 7 7 49 Midterm exam 1 3 3 Preparation for Final exam 1 18 18 Course hours 14 3 42 Individual or group work 14 2 28 Preparation for Midterm exam 1 12 12 Final exam 1 3 3 Total Workload: 155 Total Workload / 30: 155 / 30 5.17 ECTS Credits of the Course: 5