Generation of Synthetic Network Traffic Series Using a Transformed Autoregressive Model Based Adaptive Algorithm

2019 ◽  
Vol 17 (08) ◽  
pp. 1268-1275
Author(s):  
Alisson Assis Cardoso ◽  
Flavio Henrique Teles Vieira
Keyword(s):  
Network Traffic ◽  
Adaptive Algorithm ◽  
Autoregressive Model ◽  
Synthetic Network ◽  
Model Based

scholarly journals A mixture autoregressive model based on Gaussian and Student’s t-distributions

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Savi Virolainen
Keyword(s):  
Interest Rate ◽  
Autoregressive Model ◽  
Autoregressive Models ◽  
Federal Funds ◽  
Treasury Bill ◽  
Federal Funds Rate ◽  
Empirical Application ◽  
Model Based ◽  
Interest Rate Spread ◽  
Student’S T

Abstract We introduce a new mixture autoregressive model which combines Gaussian and Student’s t mixture components. The model has very attractive properties analogous to the Gaussian and Student’s t mixture autoregressive models, but it is more flexible as it enables to model series which consist of both conditionally homoscedastic Gaussian regimes and conditionally heteroscedastic Student’s t regimes. The usefulness of our model is demonstrated in an empirical application to the monthly U.S. interest rate spread between the 3-month Treasury bill rate and the effective federal funds rate.

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