Package dev.nm.stat.timeseries.linear.univariate.stationaryprocess.armagarch

Class Summary

Class	Description
AR1GARCH11Model	An AR1-GARCH11 model takes this form. \[ X_t = \mu + \phi X_{t-1} + \epsilon_t \\ h_t = \alpha_0 + \alpha_1 e_{t-1}^2 + \beta_1 h_{t-1} \]
ARMAGARCHFit	This implementation fits, for a data set, an ARMA-GARCH model by Quasi-Maximum Likelihood Estimation.
ARMAGARCHModel	An ARMA-GARCH model takes this form: \[ X_t = \mu + \sum_{i=1}^p \phi_i X_{t-i} + \sum_{i=1}^q \theta_j \epsilon_{t-j} + \epsilon_t, \\ \epsilon_t = \sqrt{h_t\eta_t}, \\ h_t = \alpha_0 + \sum_{i=1}^{r} (\alpha_i e_{t-i}^2) + \sum_{i=1}^{s} (\beta_i h_{t-i}) \]