A course in mathematical statistics and large sample theory /
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Author / Creator: | Bhattacharya, Rabi, author. |
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Imprint: | New York, NY : Springer, 2016. |
Description: | 1 online resource (xi, 389 pages) : illustrations (some color) |
Language: | English |
Series: | Springer texts in statistics, 1431-875X Springer texts in statistics, |
Subject: | Mathematical statistics. Sampling (Statistics) Maths for computer scientists. Probability & statistics. Mathematical & statistical software. Life sciences: general issues. Computers -- Mathematical & Statistical Software. Business & Economics -- Statistics. Mathematics -- Probability & Statistics -- General. Science -- Life Sciences -- General. Mathematical statistics. Sampling (Statistics) Electronic books. |
Format: | E-Resource Book |
URL for this record: | http://pi.lib.uchicago.edu/1001/cat/bib/11265443 |
Table of Contents:
- 1 Introduction
- 2 Decision Theory
- 3 Introduction to General Methods of Estimation
- 4 Sufficient Statistics, Exponential Families, and Estimation
- 5 Testing Hypotheses
- 6 Consistency and Asymptotic Distributions and Statistics
- 7 Large Sample Theory of Estimation in Parametric Models
- 8 Tests in Parametric and Nonparametric Models
- 9 The Nonparametric Bootstrap
- 10 Nonparametric Curve Estimation
- 11 Edgeworth Expansions and the Bootstrap
- 12 Frechet Means and Nonparametric Inference on Non-Euclidean Geometric Spaces
- 13 Multiple Testing and the False Discovery Rate
- 14 Markov Chain Monte Carlo (MCMC) Simulation and Bayes Theory
- 15 Miscellaneous Topics
- Appendices
- Solutions of Selected Exercises in Part 1.