পদ্ধতির তুলনা করুন

	ARIMA (Autoregressive Integrated Moving Average) মডেল	কপूला মডেল (গাউসিয়ান, t, ক্লেটন, গাম্বেল, ফ্র্যাঙ্ক)	চরম মান তত্ত্ব (Extreme Value Theory - EVT)
ক্ষেত্র	অর্থমিতি	অর্থায়ন	অর্থায়ন
পরিবার	Regression model	Regression model	Regression model
উদ্ভবের বছর	2015	1959	2001
প্রবর্তক	Box & Jenkins (Box-Jenkins methodology)	Sklar (1959); dependence-concept treatment by Joe (1997)	Coles (textbook treatment); McNeil, Frey & Embrechts
ধরন	Univariate time-series model	Dependence model	Tail / extreme-event model
মৌলিক উৎস	Box, G. E. P., Jenkins, G. M., Reinsel, G. C. & Ljung, G. M. (2015). Time Series Analysis: Forecasting and Control (5th ed.). Wiley. ISBN: 978-1118675021	Sklar, A. (1959). Fonctions de répartition à n dimensions et leurs marges. Publications de l'Institut Statistique de l'Université de Paris, 8, 229-231.	Coles, S. (2001). An Introduction to Statistical Modeling of Extreme Values. Springer. ISBN: 978-1852334598
অপর নাম	Box-Jenkins model, ARIMA(p,d,q), ARIMA Modeli	copulas, dependence copulas, vine copulas, Kopula Modelleri (Gaussian, t, Clayton, Gumbel, Frank)	EVT, generalized extreme value, generalized Pareto distribution, peaks over threshold
সম্পর্কিত	5	5	5
সারসংক্ষেপ	ARIMA 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.	Extreme Value Theory is a statistical framework for modelling the rare events that live in the tail of a probability distribution. As developed in Coles (2001) and applied to risk by McNeil, Frey & Embrechts (2005), it offers two standard routes: the Generalized Extreme Value (GEV) distribution for block maxima and the Generalized Pareto Distribution (GPD), used in the peaks-over-threshold approach, for exceedances above a high threshold.