Results 181 to 190 of about 5,691 (212)

Analysing inflation by the fractionally integrated ARFIMA-GARCH model

Journal of Applied Econometrics, 1996
This paper considers the application of long-memory processes to describing inflation for 10 countries. We implement a new procedure to obtain approximate maximum likelihood estimates of an ARFIMA-GARCH process; which is fractionally integrated I(d) with a superimposed stationary ARMA component in its conditional mean.
Baillie, Richard T, Chung, Ching-Fan, Tieslau, Margie A   +2 more
openaire   +2 more sources

A Novel Prediction Method for ARFIMA Processes

2011 International Conference on Computational and Information Sciences, 2011
The class of autoregressive fractionally integrated moving average (ARFIMA) model is an important type of long memory processes which are widely used in many fields. In this paper, a novel nonparametric method is proposed to predict ARFIMA processes based on phase space reconstruction theory and multivariate local linear estimator.
Wangyong Lv, Huiqi Wang
openaire   +1 more source

DIFFERENTIAL GEOMETRY OFARFIMAPROCESSES

Communications in Statistics - Theory and Methods, 2001
Autoregressive fractionally integrated moving average (ARFIMA) processes are widely used for modeling time series exhibiting both long-memory and short-memory behavior. Properties of Toeplitz matrices associated with the spectral density functions of Gaussian ARFIMAprocesses are used to compute differential geometric quantities.
openaire   +1 more source

ARFIMA modely časových řad

2014
The thesis deal with long-memory processes which are defined by several ways. The main concern is dedicated to ARFIMA model, to its basic properties and its application. Next, graphical, semiparametric and parametric estimation methods of ARFIMA parameters are described in detail.
openaire   +2 more sources

Network Anomaly Detection Based on ARFIMA Model

2015
In this paper, the estimation model ARFIMA is presented as a method of detecting anomalies in network traffic. Parameters estimation and model identification are performed with the use of algorithms of: Geweke and Porter-Hudak (estimation of the differencing parameters) and Box-Jankins (identification of the row of the model).
Tomasz Andrysiak, Łukasz Saganowski
openaire   +1 more source

Adaptive ARFIMA Models of Inflation

SSRN Electronic Journal, 2011
Claudio Morana, Richard Baillie
openaire   +1 more source

Spectral Methods for Fractional Arfima Processes

2002
Nel presente lavoro, nella finalità di stimare il parametro di lunga memoria di un processo ARIMA frazionale, ci si avvale di metodologie basate sulla decomposizione ortogonale del processo temporale. In particolare si propone un’integrazione dell’analisi di Fourier con l’espansione di Karhunen-Loève e con la trasformata discreta wavelet al fine di ...
COLI, Mauro, FONTANELLA, Lara, GRANTURCO M.   +2 more
openaire   +1 more source

ARFIMA model decomposition for hydrological time series

2004
In questo lavoro viene proposta una procedura statistica per la decomposizione di processi ARFIMA(p,d,q) in componenti elementari. Il problema viene ricondotto a quello della decomposizione di un processo ARMA(p+1,q+1) sfruttando il modello ARMA(1,1) come ’proxy’ della componente di lunga memoria.
CORDUAS, MARCELLA, PICCOLO, DOMENICO
openaire   +1 more source

A Hybrid ARFIMA Wavelet Artificial Neural Network Model for DJIA Index Forecasting

Computational Economics, 2022
Heni Boubaker, Stephen M Miller, Giorgio Canarella   +2 more
exaly  

Estimação de parametros em modelos ARFIMA

2021
openaire   +1 more source