Large Sample Techniques for Statistics

This book offers a comprehensive guide to large sample techniques in statistics. More importantly, it focuses on thinking skills rather than just what formulae to use; it provides motivations, and intuition, rather than detailed proofs; it begins with very simple techniques, and connects theory and...

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Bibliographic Details
Main Author: Jiang, Jiming (Author)
Corporate Author: SpringerLink (Online service)
Format: Electronic eBook
Language:English
Published: New York, NY : Springer New York, 2010.
Edition:1.
Series:Springer Texts in Statistics,
Subjects:
Online Access:Full Text via HEAL-Link
Table of Contents:
  • 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.