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Large Sample Techniques for Statistics

Large Sample Techniques for Statistics


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About the Book

The ?-? Arguments.- Modes of Convergence.- Big O, Small o, and the Unspecified c.- Asymptotic Expansions.- Inequalities.- Sums of Independent Random Variables.- Empirical Processes.- Martingales.- Time and Spatial Series.- Stochastic Processes.- Nonparametric Statistics.- Mixed Effects Models.- Small-Area Estimation.- Jackknife and Bootstrap.- Markov-Chain Monte Carlo.
About the Author: Jiming Jiang is a Professor of Statistics at the University of California, Davis. He is a Fellow of the American Statistical Association and a Fellow of the Institute of Mathematical Statistics. He is the author of another Springer book, Linear and Generalized Linear Mixed Models and Their Applications (2007). Jiming Jiang is a prominent researcher in the fields of mixed effects models, small area estimation and model selection. Most of his research papers have involved large sample techniques. He is currently an Associate Editor of the Annals of Statistics.


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Product Details
  • ISBN-13: 9781461426233
  • Publisher: Springer
  • Publisher Imprint: Springer
  • Edition: 2010 ed.
  • Language: English
  • Returnable: Y
  • Spine Width: 32 mm
  • Width: 156 mm
  • ISBN-10: 1461426235
  • Publisher Date: 05 Sep 2012
  • Binding: Paperback
  • Height: 234 mm
  • No of Pages: 610
  • Series Title: Springer Texts in Statistics
  • Weight: 915 gr


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