vbid/9783319390659

Description

The contributors to this volume include many of the distinguished researchers in this area. Many of these scholars have collaborated�with Joseph McKean to develop underlying theory for these methods,�obtain small sample corrections, and develop efficient algorithms�for their computation.�The papers cover the scope of the area, including�robust nonparametric rank-based procedures through Bayesian and big data�rank-based analyses.�Areas of application include biostatistics and�spatial areas. Over the last 30 years, robust rank-based and nonparametric methods have developed considerably.�These procedures generalize traditional Wilcoxon-type methods for one- and�two-sample location problems.�Research into these procedures has culminated in complete analyses for many�of the models used in practice including linear, generalized linear, mixed,�and nonlinear models. Settings are both multivariate and univariate.�With the development of R packages in these areas, computation of these procedures is easily�shared with readers and implemented. This book is developed from the International Conference on Robust Rank-Based and Nonparametric Methods, held at Western Michigan University in April 2015.�Typham this is the title: Robust Rank-Based and Nonparametric Methods Michigan, USA, April 2015: Selected, Revised, and Extended Contributions