Algorithms and complexity for least median of squares regression
โ Scribed by J.M. Steele; W.L. Steiger
- Publisher
- Elsevier Science
- Year
- 1986
- Tongue
- English
- Weight
- 394 KB
- Volume
- 14
- Category
- Article
- ISSN
- 0166-218X
No coin nor oath required. For personal study only.
๐ SIMILAR VOLUMES
Least median of squares (LMS) regression is a robust method to fit equations to observed data (typically in a linear model). This paper describes an approximation algorithm for LMS regression. The algorithm generates a regression solution with median residual no more than twice the optimal median re
The program LMSMVE performs robust regression analysis by using the method of the least median of squares. It also computes robust distances to locate leverage points. that is. outliers with respect to the set of independent variables. LMSMVE constructs plots of least median of squares residuals aga