This paper addresses the issue of quantifying the frequency domain accuracy of ARMA spectral estimates as dictated by the Cramér–Rao Lower Bound (CRLB). Classical work in this area has led to expressions that are asymptotically exact as both data length and model order tend to infinity, although they are commonly used in finite model order and finite data length settings as approximations. More...

This paper selects the daily return data of CSI 300 index from January 2, 2014 to September 30, 2020 study characteristics volatility. An ARMA(3,3) model was fitted log returns using R software, and ARCH effect found exist. The were then with an ARMA(3,3)-GARCH(1,1) model, fitting tested, finally short-term predicted. results empirical analysis show that series has such as non-normal distributi...

This article presents a hybrid method of structural modal parameter identification, based on improved empirical mode decomposition (EMD) and autoregressive moving average (ARMA). Special attention is given to some implementation issues, such as the mixing, false modes, judgment real intrinsic function (IMF) classical EMD, difficulty fixing order ARMA. To resolve existing defects an EMD (IEMD) t...

Laser-Doppler Anemometry (LDA) is used to measure the velocity of gases and liquids with observations irregularly spaced in time. Equidistant resampling turns out to be better than slotting techniques. After resampling, two ways of spectral estimation are compared. The first estimate is a windowed periodogram and the second is the spectrum of a time series model. That is an estimated autoregres...

–In the present work two popular methods for modelling a system are compared using modelling of Air Separation Unit (ASU). To Model any MIMO system in general both ARMA and Subspace Identification methods can be used, and the optimum results can be achieved only after thorough investigation in the actual process of the system and the methodology by which the modelling can be done so as to suit ...

There are many situations in which indicators of changes or anomalies in communication networks can be helpful, e.g. in the identification of faults. A dynamic communication network is characterised as a series of graphs with vertices representing IP addresses and edges representing information exchange between these entities weighted by packets sent. Ten graph distance metrics are used to crea...

In the recent years, the use of GARCH type (especially, ARMA-GARCH) models and computational-intelligence-based techniques—Support Vector Machine (SVM) and Relevance Vector Machine (RVM) have been successfully used for financial forecasting. This paper deals with the application of ARMA-GARCH, recurrent SVM (RSVM) and recurrent RVM (RRVM) in volatility forecasting. Based on RSVM and RRVM, two G...

Autoregressive moving average (ARMA) modeling has been used in many fields. This paper presents an approach to time series analysis of a general ARMA model parameters estimation. The proposed technique is based on the singular value decomposition (SVD) of a covariance matrix of a third order cumulants from only the output sequence. The observed data sequence is corrupted by additive Gaussian no...

In this paper we propose a test for a set of linear restrictions in a Vector Autoregressive Moving Average (VARMA) model. This test is based on the autoregressive metric, a notion of distance between two univariate ARMA models, M0 and M1, introduced by Piccolo in 1990. In particular, we show that this set of linear restrictions is equivalent to a null distance d(M0,M1) between two given ARMA mo...

Abstrac t . Some simple models are introduced which may be used for modelling or generating sequences of dependent discrete random variables with generalized Poisson marginal distribution. Our approach for building these models is similar to that of the Poisson ARMA processes considered by Al-Osh and Alzaid (1987, J. Time Ser. Anal., 8, 261-275; 1988, Statist. Hefte, 29, 281-300) and McKenzie (...