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Books > Science & Mathematics > Biology, life sciences > Life sciences: general issues
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Robust Rank-Based and Nonparametric Methods - Michigan, USA, April 2015: Selected, Revised, and Extended Contributions (Paperback, Softcover reprint of the original 1st ed. 2016)
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Robust Rank-Based and Nonparametric Methods - Michigan, USA, April 2015: Selected, Revised, and Extended Contributions (Paperback, Softcover reprint of the original 1st ed. 2016)
Series: Springer Proceedings in Mathematics & Statistics, 168
Expected to ship within 10 - 15 working days
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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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