Results 71 to 80 of about 367 (185)
Prediction intervals in the ARFIMA model using bootstrap G
Financial Statistical Journal, 2018 This paper presents a bootstrap resampling scheme to build pre-diction intervals for future values in fractionally autoregressive movingaverage (ARFIMA) models. Standard techniques to calculate forecastintervals rely on the assumption of normality of the data and do nottake into account the uncertainty associated with parameter estima-tion.
Glaura C. Franco +2 more
openaire +2 more sources
Inflação inercial sob mudanças de regime: análise a partir de um modelo MS-ARFIMA, 1944-2009
Economia Aplicada, 2011 Este artigo analisa a dinâmica da inflação brasileira a partir de uma estrutura fracionária com mudança de regime markoviana, MS-ARFIMA, fornecida por Tsay & W. (2009).
Erik Alencar de Figueiredo +1 more
doaj +1 more source
Frontiers in Systems Neuroscience, 2019 Electroencephalogram (EEG) undergoes complex temporal and spectral changes during voluntary movement intention. Characterization of such changes has focused mostly on narrowband spectral processes such as Event-Related Desynchronization (ERD) in the ...
Maitreyee Wairagkar +2 more
doaj +1 more source
Sèries temporals amb memòria llarga: models ARFIMA
, 2023 Treballs Finals de Grau de Matemàtiques, Facultat de Matemàtiques, Universitat de Barcelona, Any: 2023 , Director: Josep Vives i Santa ...
openaire +1 more source
Modeling of nonstationarity and long memory with RS-ARFIMA-GARCH model
African Journal of Applied Statistics, 2018 We consider in this study the problem of confusion between the nonstationarity and the long memory. Many authors have pointed out, in empirical case, the existence of long memory in financial and economics time series, through processes supposed short memory stationary (See Mikosch and Stáricá (2004) and Lobato and Savin (1998)).
FOFANA, Souleymane +2 more
openaire +2 more sources
Jurnal Matematika Integratif, 2019 Investors having an understanding of investment statistics are important. Especially quantitative tools related to investment risk measurement. Value-at-Risk Adjusted is one of the investment risk measurement tools, which assumes that returns are not ...
F Sukono +4 more
doaj +1 more source
Coal consumption forecast based on fractional ARIMA model
矿业科学学报, 2017 The consumption of coal is very complex, and the forecast and analysis of coal consumption can provide reference for rational arrangement of coal production.The usual prediction is based on the ARMA or ARIMA model, which neither consider its long-term ...
Liu Kai, Zhang Xi
doaj +1 more source
Vietnam Journal of Science, Technology and EngineeringThis study establishes the efficiency of the maintenance workforce in a process plant, utilising combined models, including artificial neural networks (ANN)-weighted aggregated sum product assessment (WASPAS) and ANN-fuzzy inference system (FIS)-WASPAS.
Sunday Ayoola Oke +1 more
doaj
Stock market volatility simulation with the LSTM neural network
Вестник Пермского университета: Серия ЭкономикаIntroduction. Stock market volatility simulation and forecast are relevant issues which could contribute into lower risks and higher revenues of the market transactions.
Dmitry Aleksandrovich Patlasov +1 more
doaj +1 more source
Estimating the Degree of Integration in CPI with ARFIMA-FIGARCH Model: Case study of Iran [PDF]
Faslnāmah-i Pizhūhish/Nāmah-i Iqtisādī, 2014 The study of the effect of memory in different economic indices, especially inflation and money market, has high research attractiveness. In this paper, by using the data of consumer price index for Iran during 1990/04 – 2011/11, we investigate the ...
Hossein Abbasinejad +1 more
doaj