Results 91 to 100 of about 7,220 (228)
Aquila Optimizer‐Based Hybrid Predictive Model for Traffic Congestion in an IoT‐Enabled Smart City
International Journal of Intelligent Systems, Volume 2024, Issue 1, 2024.Effective traffic congestion prediction is need of the hour in a modern smart city to save time and improve the quality of life for citizens. In this study, AB_AO (ARIMA Bi‐LSTM using Aquila optimizer), a hybrid predictive model, is proposed using the most effective time‐series data prediction statistical model ARIMA (Autoregressive Integrated Moving ...
Ayushi Chahal +4 more
wiley +1 more source
Modelling and Forecasting Noisy Realized Volatility [PDF]
Several methods have recently been proposed in the ultra high frequency financial literature to remove the effects of microstructure noise and to obtain consistent estimates of the integrated volatility (IV) as a measure of ex-post daily volatility. Even
Asai, M., McAleer, M.J., Medeiros, M.
core +4 more sources
Kripto Para Birimi Piyasalarında GPH Yöntemi ile Uzun Hafıza Analizi: Bitcoin Örneği
Ekonomi, Politika & Finans Araştırmaları DergisiSon yıllarda, para piyasalarında ve bankacılık sektöründe yaşanan krizlerin etkisiyle merkezi para otoritelerine olan güven sarsılmış ve bu nedenle merkezi olmayan bir sistem arayışına girilmiştir.
İpek Yurttagüler
doaj +1 more source
Lecturas de Economía, 2011 Sesgos en estimación, tamaño y potencia de una prueba sobre el parámetro de memoria larga en modelos ARFIMA Resumen: Castaño et al. (2008) proponen una prueba para investigar la existencia de memoria larga, basada en el parámetro de diferenciación ...
Elkin Castaño Vélez +2 more
doaj +1 more source
Does the ARFIMA really shift? [PDF]
, 2017 Short memory models contaminated by level shifts have long-memory features similar to those associated to processes generated under fractional integration. In this paper, we propose a robust testing procedure, based on an encompassing parametric specification, that allows to disentangle the level shift term from the ARFIMA component.
Monache, Davide Delle +2 more
openaire
On the invertibility in periodic ARFIMA models
, 2020 The present paper, characterizes the invertibility and causality conditions of a periodic ARFIMA (PARFIMA) models. We first, discuss the conditions in the multivariate case, by considering the corresponding p-variate stationary ARFIMA models. Second, we construct the conditions using the univariate case and we deduce a new infinite autoregressive ...
Amimour, Amine, Belaide, Karima
openaire +2 more sources
Revista de Economia e Sociologia Rural, 2007 O presente trabalho tem como objetivo modelar séries temporais para efeito de previsão com diferenciações inteira e fracionária, utilizando dados de preços futuros de commodities agrícolas.
Ricardo Chaves Lima +2 more
doaj +1 more source
Estimation of parameters in ARFIMA processes
, 2020 It is known that, in the presence of short memory components, the estimation of the fractional parameter d in an Autoregressive Fractionally Integrated Moving Average, ARFIMA(p, d, q), process leads to some difficulties (Smith et al. (1997)). In this paper, we continue the efforts made by Smith et al. (1997) by conducting a simulation study to evaluate
Lopes, Silvia Regina Costa +2 more
openaire +1 more source
Error and Model Misspecification in ARFIMA Process
Brazilian Review of Econometrics, 2001 In developing the long and short memory estimation, it is usually assumed that the innovations in the ARFIMA model are normally distributed. However, circumstances may occur where this assumption is not true. This paper uses Monte Carlo simulation to evaluate the robustness of different estimators of the fractional parameter in stationary and ...
Valderio A. Reisen +2 more
openaire +2 more sources
Minimum distance estimation of stationary and non-stationary ARFIMA processes [PDF]
A new parametric minimum distance time-domain estimator for ARFIMA processes is introduced in this paper. The proposed estimator minimizes the sum of squared correlations of residuals obtained after filtering a series through ARFIMA parameters.
Laura Mayoral
core