The challenge of predicting future values of a time series covers a variety of disciplines. The fundamental problem of selecting the order and identifying the time varying parameters of an autoregressive moving average model (ARMA) concerns many important fields of interest such as linear prediction, system identification and spectral analysis. Recent research activities in forecasting with art...

In software-defined networking (SDN), the control layers are moved away from forwarding switching layers. SDN gives more programmability and flexibility to controllers. OpenFlow is a protocol that access plane of network switch or router over network. uses centralized switches routers in environment. Security major importance for deployment. Transport layer security (TLS) used implement OpenFlo...

Traditionally, the autoregressivemoving average (ARMA)model has been one of themost widely used linear models in time series prediction. Recent research activities in forecasting with artificial neural networks (ANNs) suggest that ANNs can be a promising alternative to the traditional ARMA structure. These linear models and ANNs are often compared with mixed conclusions in terms of the superior...

In this paper we develop an asymptotic theory for estimation based on signed ranks in the ARMA model when the innovation density is symmetrical. We provide two classes of estimators and we establish their asymptotic normality with the help of the asymptotic properties for serial signed rank statistics. Finally, we compare our procedure to the one of least-squares, and we illustrate the performa...

In this paper, the S&P 500 stock index is studied for its time varying volatility and stylized facts. The ARMA mean equation with asymmetric power ARCH errors is used to model the series correlations and the conditional heteroscadesticity in the asset returns. The conditional distributions of the standardized residuals are assumed to be the normal distribution, the t distribution or the skew-t ...

The pourpose of this paper is to propose the Stock Market (SM) volatility estimation method based on the Higher Order Cumulant (HOC) function, and to apply it to the cases when stock market returns have a non Gaussian distribution and/or when a distribution of SM innovations is unknown. The HOC functions of the third and fourth order are used not only as a means for non Gaussian model testing b...

The time domain solution of the equations of motion of structures subjected to a stochastic wind field is often obtained by a step-by-step integration approach. The loading is described by simulated time histories of the aerodynamic force. Recently, autoregressive and moving average (ARMA) recursive models have been utilized to simulate the time series of wind loads. Based on the system dynamic...

We present a bayesian method for the blind estimation of parameters in nonlinear/nongaussian models. The studied models are called H-ARMA processes. They are generated by a memoryless polynomial transformation of an ARMA process. The nonlinearities are choosen as Her-mite polynomials. After recalling the structure of those models and their main properties that have been reported in previous pub...