Code | DMS214 |

Name | Random Processes |

Status | Compulsory/Courses of Limited Choice |

Level and type | Undergraduate Studies, Academic |

Field of study | Mathematics and Statistics |

Faculty | |

Academic staff | Kārlis Šadurskis, Nataļja Budkina, Aija Pola, Andrejs Matvejevs, Oksana Pavļenko, Marija Dobkeviča, Jolanta Goldšteine |

Credit points | 2.0 (3.0 ECTS) |

Parts | 1 |

Annotation |
Definition and application of random process. Multivariate distributions. Correlation theory. Classification of processes. Stationary processes. Markov chain with discrete and continuous time. Markov processes. Gussian processes. Imitation of random processes.. |

Goals and objectives of the course in terms of competences and skills |
Objective of the course is to acquaint students with basics of random processes theory and its mathematical apparatus, assiduity to Markov chains allow to understand the regularities of the random dynamic phenomena. |

Learning outcomes and assessment |
Discrete time Markov chains. Ability to construct transition probability matrix and apply it for calculation of characteristics of the chain, to find stationary distribution both theoretically and with immitation model. - Problems included in homework 1 Continuous time Markov chains. Ability to construct transition density matrix and apply it for calculation of characteristics of the chain, to find stationary distribution both theoretically and with immitation model. - Problems included in homework 2 Random processes' correlation theory. Markov processes. The major know-how for analysis of Markov chains. - Problems included in the exam |

Course prerequisites |

[Extended course information PDF]