পদ্ধতির তুলনা করুন
নির্বাচিত পদ্ধতিগুলো পাশাপাশি পর্যালোচনা করুন; যে সারিগুলোয় পার্থক্য আছে সেগুলো চিহ্নিত করা হয়।
| প্রভাব নির্ণায়ক (কুকের দূরত্ব, DFFITS, লিভারেজ)× | মেডিয়ান অ্যাবসোলিউট ডেভিয়েশন (MAD) অনুমান× | কোয়ান্টাইল রিগ্রেশন× | |
|---|---|---|---|
| ক্ষেত্র≠ | পরিসংখ্যান | পরিসংখ্যান | অর্থমিতি |
| পরিবার | Regression model | Regression model | Regression model |
| উদ্ভবের বছর≠ | 1977 | 1974 | 1978 |
| প্রবর্তক≠ | R. Dennis Cook (Cook's distance); Belsley, Kuh & Welsch (DFFITS, leverage) | Hampel (influence-curve treatment); classical robust statistics | Koenker & Bassett |
| ধরন≠ | Regression diagnostic | Robust scale estimator | Conditional quantile regression |
| মৌলিক উৎস≠ | Cook, R. D. (1977). Detection of Influential Observations in Linear Regression. Technometrics, 19(1), 15-18. DOI ↗ | Hampel, F. R. (1974). The Influence Curve and Its Role in Robust Estimation. Journal of the American Statistical Association, 69(346), 383-393. DOI ↗ | Koenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50. DOI ↗ |
| অপর নাম≠ | Cook's distance, DFFITS, leverage, influential observation detection | median absolute deviation, MAD scale estimator, robust scale estimation, Medyan Mutlak Sapma (MAD) Tahmini | conditional quantile regression, regression quantiles, Kantil Regresyon |
| সম্পর্কিত | 5 | 5 | 5 |
| সারসংক্ষেপ≠ | Influence diagnostics are a family of post-fit measures that quantify how much each single observation affects a fitted regression. Cook's distance was introduced by R. Dennis Cook in 1977, with leverage and DFFITS formalised by Belsley, Kuh and Welsch in 1980, to flag the observations that most strongly pull the estimated coefficients. | Median Absolute Deviation estimation is a robust measure of statistical dispersion that replaces the standard deviation when outliers are present. Rooted in the influence-curve framework formalised by Hampel (1974), it summarises the spread of a continuous variable using medians instead of means, so a single extreme value cannot distort the result. | 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. |
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