পদ্ধতির তুলনা করুন
নির্বাচিত পদ্ধতিগুলো পাশাপাশি পর্যালোচনা করুন; যে সারিগুলোয় পার্থক্য আছে সেগুলো চিহ্নিত করা হয়।
| ARIMA (Autoregressive Integrated Moving Average) মডেল× | লোএসএস / লোএসএস স্থানীয় রিগ্রেশন× | |
|---|---|---|
| ক্ষেত্র≠ | অর্থমিতি | যন্ত্র শিখন |
| পরিবার≠ | Regression model | Machine learning |
| উদ্ভবের বছর≠ | 2015 | 1979 |
| প্রবর্তক≠ | Box & Jenkins (Box-Jenkins methodology) | William S. Cleveland |
| ধরন≠ | Univariate time-series model | Local nonparametric regression smoother |
| 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 | Cleveland, W. S. (1979). Robust locally weighted regression and smoothing scatterplots. Journal of the American Statistical Association, 74(368), 829–836. DOI ↗ |
| অপর নাম≠ | Box-Jenkins model, ARIMA(p,d,q), ARIMA Modeli | LOWESS, local regression, locally weighted scatterplot smoothing, yerel regresyon |
| সম্পর্কিত≠ | 5 | 3 |
| 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). | LOESS (locally estimated scatterplot smoothing), introduced by William Cleveland in 1979 and extended with Susan Devlin in 1988, fits a smooth curve through data by performing a separate weighted polynomial regression in the neighbourhood of each point. Nearby observations count more than distant ones, so the method follows local structure without assuming any global functional form, making it a popular exploratory smoother for scatterplots. |
| ScholarGateডেটাসেট ↗ |
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