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Forecasting of consumer demand with the use of multi-factor dynamic models
(Universidad del Zulia, 2019)
On the application of discrete-time Volterra series for the damage detection problem in initially nonlinear systems
(2017-01-01)
Nonlinearities in the dynamical behavior of mechanical systems can degrade the performance of damage detection features based on a linearity assumption. In this article, a discrete Volterra model is used to monitor the ...
Forecasting Multiple Time Series With One-Sided Dynamic Principal Components
(American Statistical Association, 2019-02)
We define one-sided dynamic principal components (ODPC) for time series as linear combinations of the present and past values of the series that minimize the reconstruction mean squared error. Usually dynamic principal ...
Noisy Chaotic time series forecast approximated by combining Reny's entropy with Energy associated to series method: Application to rainfall series
(IEEE Computer Society, 2017)
This article proposes that the combination of smoothing approach considering the entropic information provided by Renyi's method, has an acceptable performance in term of forecasting errors. The methodology of the proposed ...
Análise de séries temporais fuzzy para previsão e identificação de padrões comportamentais dinâmicos
(Universidade Federal de São CarlosUFSCarPrograma de Pós-Graduação em Ciência da Computação - PPGCCCâmpus São Carlos, 2015-04-30)
The good results obtained by the fuzzy approaches applied in the analysis of time series
(TS) has contributed significantly to the growth of the area. Although there are satisfactory
results in TS analysis with methods ...
The role of no-arbitrage on forecasting: lessons from a parametric term structure model
(Escola de Pós-Graduação em Economia da FGV, 2007-10-01)
Parametric term structure models have been successfully applied to innumerous problems in fixed income markets, including pricing, hedging, managing risk, as well as studying monetary policy implications. On their turn, ...
Physical-based time series model applied on water table depths dynamics characteristics simulation
(Assoc Brasileira Recursos Hidricos-abrh, 2017-01-01)
Time series modelling applied to study water table depths monitoring data is an elegant way to model irregular and continuous data. When successive observations are dependent, future values may be predicted from past ...
Estudo de caso da metodologia Dynamic Time Scan Forecasting para previsão da série histórica de preços da ação preferencial da Petrobrás
(Universidade Federal de Minas GeraisBrasilICX - DEPARTAMENTO DE ESTATÍSTICAPrograma de Pós-Graduação em EstatísticaUFMG, 2021-08-23)
Motivated by the capacity of the Dynamic Time Scan Forecasting (DTSF) method in identifying patterns through statistical similarity functions in order to build forecasts in time series, this work proposes to study its ...