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U-Statistics, MM-Estimators and Resampling

U-Statistics, MM-Estimators and Resampling


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About the Book

This is an introductory text on a broad class of statistical estimators that are minimizers of convex functions. It covers the basics of U-statistics and Mm-estimators and develops their asymptotic properties. It also provides an elementary introduction to resampling, particularly in the context of these estimators. The last chapter is on practical implementation of the methods presented in other chapters, using the free software R.


About the Author:

Arup Bose is Professor at the Statistics and Mathematics Unit, Indian Statistical Institute, Kolkata, India. He is a Fellow of the Institute of Mathematical Statistics and of all the three national science academies of India. He has significant research contributions in the areas of statistics, probability, economics and econometrics. He is a recipient of the Shanti Swarup Bhatnagar Prize and the C R Rao National Award in Statistics. His current research interests are in large dimensional random matrices, free probability, high dimensional data, and resampling. He has authored three books: Patterned Random Matrices, Large Covariance Autocovariance Matrices (with Monika Bhattacharjee) and (with Koushik Saha), published by Chapman & Hall.

Snigdhansu Chatterjee is Professor at the School of Statistics, University of Minnesota, USA. He is also the Director of the Institute for Research in Statistics and its Applications. His research interests are in resampling methods, high-dimensional and big data statistical methods, small area methods, and application of statistics in climate science, neuroscience and social sciences. He has written over 45 research articles.


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Product Details
  • ISBN-13: 9789811347566
  • Publisher: Springer
  • Binding: Paperback
  • Language: English
  • Returnable: Y
  • Spine Width: 10 mm
  • Width: 156 mm
  • ISBN-10: 9811347565
  • Publisher Date: 01 Feb 2019
  • Height: 234 mm
  • No of Pages: 174
  • Series Title: Texts and Readings in Mathematics
  • Weight: 326 gr


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