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...

A new method for the identification of the nonlinear Hammerstein Model consisting a static nonlinearity in cascade with a linear dynamic part, is introduced. The static nonlinearity is modeled by radial basis function neural networks (RBFNN) and the linear part is modeled by an autoregressive moving average (ARMA) model. A recursive algorithm is developed to update the weights of the RBFNN and ...

A powerful parametric spectral estimation technique, 2D-ARMA (Auto Regressive Moving Average) modeling, has been applied to contrast transfer function (CTF) detection in electron microscopy. Parametric techniques such as AR (auto regressive) and ARMA models allow a more exact determination of the CTF than traditional methods based only on the Fourier Transform (FT). Previous works revealed that...

We express the classic ARMA time-series model as a directed graphical model. In doing so, we find that the deterministic relationships in the model make it effectively impossible to use the EM algorithm for learning model parameters. To remedy this problem, we replace the deterministic relationships with Gaussian distributions having a small variance, yielding the stochastic ARMA (σARMA) model....

In this paper, a new method of estimation of the magnitude square coherence function (MSC) by an ARMA model is proposed. The estimation is achieved by modeling the periodogram estimate of the MSC and the ARMA model has been realized by the pole-zero decomposition property of the group delay function (GDF). Its performance has been found to be superior to that of the periodogram MSC estimate in ...

This paper reports the feasibility of the ARMA model to describe a bursty video source transmitting over a AAL5 ATM link (VBR traffic). The traffic represents the activity of the action movie "Lethal Weapon 3" transmitted over the ATM network using the Fore System AVA-200 ATM video codec with a peak rate of 100 Mbps and a frame rate of 25. The model parameters were estimated for a single video ...

We propose in this paper an original technique to predict global radiation using a hybrid ARMA/ANN model and data issued from a numerical weather prediction model (ALADIN). We particularly look at the Multi-Layer Perceptron. After optimizing our architecture with ALADIN and endogenous data previously made stationary and using an innovative pre-input layer selection method, we combined it to an ...

Abstract. Conventional streamflow models operate under the assumption of constant variance or season-dependent variances (e.g. ARMA (AutoRegressive Moving Average) models for deseasonalized streamflow series and PARMA (Periodic AutoRegressive Moving Average) models for seasonal streamflow series). However, with McLeod-Li test and Engle’s Lagrange Multiplier test, clear evidences are found for t...

Discrete time-varying autoregressive moving average (ARMA) models are used to describe realistic earthquake ground motion time histories. Both amplitude and frequency nonstationarities are incorporated in the model. An iterative Kalman filtering scheme is introduced to identify the time-varying parameters of an ARMA model from an actual earthquake record. Several model verification tests are pe...