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Linganisha mbinu

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Mfumo wa ARIMA (Autoregressive Integrated Moving Average)×Mifumo ya kopula (Gaussiani, t, Clayton, Gumbel, Frank)×
NyanjaEkonometrikiFedha
FamiliaRegression modelRegression model
Mwaka wa asili20151959
MwanzilishiBox & Jenkins (Box-Jenkins methodology)Sklar (1959); dependence-concept treatment by Joe (1997)
AinaUnivariate time-series modelDependence model
Chanzo asiliaBox, G. E. P., Jenkins, G. M., Reinsel, G. C. & Ljung, G. M. (2015). Time Series Analysis: Forecasting and Control (5th ed.). Wiley. ISBN: 978-1118675021Sklar, A. (1959). Fonctions de répartition à n dimensions et leurs marges. Publications de l'Institut Statistique de l'Université de Paris, 8, 229-231. link ↗
Majina mbadalaBox-Jenkins model, ARIMA(p,d,q), ARIMA Modelicopulas, dependence copulas, vine copulas, Kopula Modelleri (Gaussian, t, Clayton, Gumbel, Frank)
Zinazohusiana55
MuhtasariARIMA is a univariate time-series forecasting model that combines autoregressive, integrated (differencing), and moving-average components to predict a single continuous series from its own past. It is the centrepiece of the Box-Jenkins methodology set out in Box, Jenkins, Reinsel & Ljung's Time Series Analysis (5th ed., 2015).Copula models are a family of functions that describe the dependence structure between variables separately from their individual (marginal) distributions. The foundation is Sklar's theorem (1959), which shows that any multivariate distribution can be split into its marginals plus a copula; Joe (1997) developed the modern catalogue of dependence concepts. They are central to portfolio risk and credit modelling.
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ScholarGateLinganisha mbinu: ARIMA · Copula Models. Imepatikana 2026-06-19 kutoka https://scholargate.app/sw/compare