wwcode
Rank-Based Analysis of Linear Models Using R. It is well-known that Wilcoxon procedures out perform least squares procedures when the data deviate from normality and/or contain outliers. These procedures can be generalized by introducing weights; yielding so-called weighted Wilcoxon (WW) techniques. In this paper we demonstrate how WW-estimates can be calculated using an L1 regression routine. More importantly, we present a collection of functions that can be used to implement a robust analysis of a linear model based on WW-estimates. For instance, estimation, tests of linear hypotheses, residual analyses, and diagnostics to detect differences in fits for various weighting schemes are discussed. We analyze a regression model, designed experiment, and autoregressive time series model for the sake of illustration. We have chosen to implement the suite of functions using the R statistical software package. Because R is freely available and runs on multiple platforms, WW-estimation and associated inference is now universally accessible.
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References in zbMATH (referenced in 18 articles , 1 standard article )
Showing results 1 to 18 of 18.
Sorted by year (- Yang, Jing; Lu, Fang; Yang, Hu: Local Walsh-average-based estimation and variable selection for single-index models (2019)
- Auda, Hend A.; Ismail, Mohamed A.; Rashed, Ali A.: Wilcoxon rank based principal component analysis (2018)
- Du, Jiang; Zhang, Zhongzhan; Xie, Tianfa: Model averaging for M-estimation (2018)
- Zhang, Qingzhao; Duan, Xiaogang; Ma, Shuangge: Focused information criterion and model averaging with generalized rank regression (2017)
- Zhang, Qing Zhao; Duan, Xiao Gang; Zhou, Xiao Hua: A weighted Wilcoxon estimate for the covariate-specific ROC curve (2017)
- Denhere, Melody; Bindele, Huybrechts F.: Rank estimation for the functional linear model (2016)
- Feng, Long; Zou, Changliang; Wang, Zhaojun; Wei, Xianwu; Chen, Bin: Robust spline-based variable selection in varying coefficient model (2015)
- Feng, Long; Zou, Changliang; Wang, Zhaojun; Zhu, Lixing: Robust comparison of regression curves (2015)
- Yang, Hu; Guo, Chaohui; Lv, Jing: SCAD penalized rank regression with a diverging number of parameters (2015)
- Zhu, Neng-Hui: Two-stage local Walsh average estimation of generalized varying coefficient models (2015)
- Feng, Long; Zou, Changliang; Wang, Zhaojun: Local Walsh-average regression (2012)
- Wang, Haiyan; Tolos, Siti; Wang, Suojin: A distribution free test to detect general dependence between a response variable and a covariate in the presence of heteroscedastic treatment effects (2010)
- Roelant, E.; van Aelst, S.; Croux, C.: Multivariate generalized S-estimators (2009)
- Gao, Xin; Alvo, Mayer: Nonparametric multiple comparison procedures for unbalanced two-way layouts (2008)
- Gao, Xin; Alvo, Mayer; Chen, Jie; Li, Gang: Nonparametric multiple comparison procedures for unbalanced one-way factorial designs (2008)
- Omelka, Marek: Second-order linearity of Wilcoxon statistics (2007)
- Jeff Terpstra; Joseph McKean: Rank-Based Analysis of Linear Models Using R (2005) not zbMATH
- McKean, Joseph W.: Robust analysis of linear models (2004)