MMS3442 - Pengantar Proses Stokastik - Danardono

Capaian Pembelajaran

Ilustrasi tujuan pembelajaran

By the end of this course, the students will be able to:


CO1. explain essential concepts in stochastic processes; discuss real life examples of stochastic processes (Random Walk, Markov-Chains, Poisson Processes, Birth and Death Procesess)
CO2. formulate the appropriate stochastics models for given a certain process and its assumption
CO3. implement theorems, methods and computing algorithm in a given stochastic model

 

Contents:

Stochastic Processes and Random Processes; Random Walk; Markov Chains, Transition Probabilities, Chapman-Kolmogorov Equation; Classification of States and Chains, Limiting Probabilities; Poisson Processes, Birth and Death Processes, Continuous Time Markov-Chains. Simulation and Computation




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