In this program
- Probability foundations
- Discrete-time processes
- Continuous-time processes
- Applications in finance and engineering
- Computational and statistical methods
Computational and statistical methods
Stochastic processes · Standard syllabus
Estimation for stochastic models (MLE, method of moments)
Objectives
- Estimation for stochastic models (MLE, method of moments)
- Simulation of Markov chains
- Point processes
- Time series as stochastic processes (ARMA connection)
- Numerical methods for SDEs: Euler–Maruyama and Milstein
- Case studies in biology and physics
- Operations research
Study materials
- Study guideComing soon
- Exam StrategyComing soon
- Common MistakesComing soon
- WorksheetsComing soon
- Word problemsComing soon
- Mixed PracticeComing soon
- Multi-Unit ProblemsComing soon
- ReviewComing soon
- Practice testComing soon
- Answer keyComing soon
Interactive practice
Quizzes, typed answers, and flashcards for this unit — coming soon.
- Coming soon
Quiz
Multiple-choice questions with instant feedback
- Coming soon
Typed practice
Type answers and check them
- Coming soon
Flashcards
Vocabulary and key facts
- Coming soon
Mixed quiz
Harder mixed review for this standard