Time Series. Modelling of Stochastic Processes and Numerical Methods

Descipline Time Series. Modelling of Stochastic Processes and Numerical Methods
Faculty Faculty of Mechanics and Mathematics
Faculty URL http://www.mechmat.univ.kiev.ua/en
Language English
Degree Master
Credits 4
Semester 3
Description This training course studies the statistics of time series based on the use of linear models AR (p), MA (q), ARMA (p, q), nonlinear models ARIMA (p, d, q), BL (p, q, m, k), EARMA (p, q), financial time series ARCH, GARCH. The problems of finding the trends and fitting models to real data are discussed too.
The students study also the methods of construction the models of random variables, various expansions of random processes into series and integrals: the Karhunen-Loev expansions, expansions into series with uncorrelated terms, spectral expansions of stationary processes, using such expansions for constructions the models for random processes, finding accuracy and reliability of approximation by this models of random processes.
Teachers Maiboroda Rostislav
Department of Probability Theory, Statistics and Actuarial Mathematics,
Faculty of Mechanics and Mathematics,
Phone:
+380442590392
e-mail:
mre@univ.kiev.ua
Author: admin