Modelling with Random Processes
Course: Modelling with Random Processes
ECTS points: 6 ЕКТС
Number of classes per week: 3+0+0+3
Lecturer: Prof. Dr. Aneta Buchkovska
Course Goals (acquired competencies): The student is expected to recognize the type of the process in real problems. It is capable of creating a mathematical model and solving it.
Course Syllabus: Renewable Processes. Birth and Dying Processes. Markov process with two states. Markov process with multiple states. Hidden Markov process. Binomial and Poisson model. Glad and statistical tests. Methods of starvation. Exposure to risk. Heterogeneity in the population. Selection. Application: DNA sequence and genetic networks; Claims and consumption data; Prediction for web pages.
|Wai-Ki Ching Michael K. Ng||Markov Chains: Models, Algorithms and Applications||Springer Science&Business Media, Inc||2006|