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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Robust Rank-Based and Nonparametric Methods: Michigan, Usa, April 2015: Selected, Revised, and Extended Contributions

Robust Rank-Based and Nonparametric Methods: Michigan, Usa, April 2015: Selected, Revised, and Extended Contributions

McKean, Joseph W.
Liu, Regina Y.

Paperback

Series: Springer Proceedings in Mathematics & Statistics, Book 168

Medical ReferenceGeneral ScienceProbability & Statistics

ISBN10: 3319818090
ISBN13: 9783319818092
Publisher: Springer
Published: Jun 14 2018
Pages: 277
Weight: 0.91
Height: 0.61 Width: 6.14 Depth: 9.21
Language: English

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.

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