পদ্ধতির তুলনা করুন

	ARFIMA: ভগ্নাংশিক সমাকলিত ARMA মডেল	কোয়ান্টাইল রিগ্রেশন
ক্ষেত্র	অর্থমিতি	অর্থমিতি
পরিবার	Regression model	Regression model
উদ্ভবের বছর	1980	1978
প্রবর্তক	Granger & Joyeux (1980); Hosking (1981)	Koenker & Bassett
ধরন	Long-memory time series model	Conditional quantile regression
মৌলিক উৎস	Granger, C. W. J. & Joyeux, R. (1980). An Introduction to Long-Memory Time Series Models and Fractional Differencing. Journal of Time Series Analysis, 1(1), 15–29.	Koenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50.
অপর নাম	fractionally integrated ARMA, long-memory time series model, ARFIMA / FIGARCH, fractional differencing model	conditional quantile regression, regression quantiles, Kantil Regresyon
সম্পর্কিত	5	5
সারসংক্ষেপ	ARFIMA is a time series model that captures long-memory behaviour using a fractional differencing parameter d, generalising the integer differencing of ARIMA. It was introduced by Granger and Joyeux (1980) and formalised by Hosking (1981) to describe series whose autocorrelations decay slowly rather than abruptly.	Quantile regression models conditional quantiles of an outcome - the median, the 25th or 75th percentile, and so on - rather than the conditional mean that OLS targets. Introduced by Koenker and Bassett in 1978, it reveals how predictors act across the whole distribution, including its tails.