পদ্ধতির তুলনা করুন

	তীর্যক বিন্যাসের জন্য অ্যাডজাস্টেড বক্সপ্লট	জ্যাকনাইফ পুনঃনমুনায়ন (Jackknife Resampling)	মেডিয়ান অ্যাবসোলিউট ডেভিয়েশন (MAD) অনুমান	রোবাস্ট টাইম সিরিজ অ্যানালাইসিস
ক্ষেত্র	পরিসংখ্যান	পরিসংখ্যান	পরিসংখ্যান	পরিসংখ্যান
পরিবার	Regression model	Regression model	Regression model	Regression model
উদ্ভবের বছর	2008	1956	1974	2019
প্রবর্তক	Hubert & Vandervieren	Quenouille (1956); reviewed by Miller (1974)	Hampel (influence-curve treatment); classical robust statistics	Maronna, Martin, Yohai & Salibián-Barrera (textbook treatment); robust estimation tradition
ধরন	Robust outlier detection / descriptive visualization	Resampling / bias and variance estimation	Robust scale estimator	Robust time series model (AR / MA / ARIMA)
মৌলিক উৎস	Hubert, M. & Vandervieren, E. (2008). An Adjusted Boxplot for Skewed Distributions. Computational Statistics & Data Analysis, 52(12), 5186-5201.	Quenouille, M. H. (1956). Notes on Bias in Estimation. Biometrika, 43(3/4), 353-360.	Hampel, F. R. (1974). The Influence Curve and Its Role in Robust Estimation. Journal of the American Statistical Association, 69(346), 383-393.	Maronna, R. A., Martin, R. D., Yohai, V. J., & Salibián-Barrera, M. (2019). Robust Statistics: Theory and Methods (with R) (2nd ed.). Wiley. ISBN: 978-1119214687
অপর নাম	adjusted box plot, medcouple boxplot, skewness-adjusted boxplot, Düzeltilmiş Kutu Grafiği (Adjusted Boxplot)	leave-one-out resampling, Quenouille-Tukey jackknife, delete-one jackknife, Jackknife Yeniden Örnekleme	median absolute deviation, MAD scale estimator, robust scale estimation, Medyan Mutlak Sapma (MAD) Tahmini	robust ARIMA, robust autoregressive model, outlier-resistant time series, Robust Zaman Serisi Analizi
সম্পর্কিত	5	5	5	5
সারসংক্ষেপ	The Adjusted Boxplot is a robust descriptive tool introduced by Hubert and Vandervieren (2008) that corrects the classical IQR-based boxplot for skewness using the medcouple statistic, reducing the false labelling of outliers in asymmetric data.	The jackknife is a classical resampling method that estimates the bias and variance of a statistic by systematically recomputing it with one observation left out at a time. Introduced by Quenouille in 1956 and later reviewed by Miller in 1974, it predates the bootstrap and remains a simple, deterministic tool for assessing estimator stability.	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.	Robust Time Series Analysis fits autoregressive, moving-average, and ARIMA models to series that contain outliers or structural breaks, using M-estimation or MM-estimation instead of ordinary least squares so that a few anomalous observations do not distort the fit. It follows the robust statistics tradition consolidated in Maronna, Martin, Yohai and Salibián-Barrera (2019).