☰

Probability & Statistics

Asymptotic Statistics (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 3)

R 2,615

or 4 x payments of R653.75 with Payflex

Payflex

Availability: Currently in Stock

Delivery: 10-20 working days

Please be aware orders placed now may not arrive in time for Christmas, please check delivery times.

Condition: USED (All books are in used condition)

Condition - Very Good
The item shows wear from consistent use, but it remains in good condition and functions properly. Item may arrive with damaged packaging or be repackaged. It may be marked, have identifying markings on it, or have minor cosmetic damage. It may also be missing some parts/accessories or bundled items.

Asymptotic Statistics (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 3)
- Used Book in Good Condition
Here is a practical and mathematically rigorous introduction to the field of asymptotic statistics. In addition to most of the standard topics of an asymptotics course--likelihood inference, M-estimation, the theory of asymptotic efficiency, U-statistics, and rank procedures--the book also presents recent research topics such as semiparametric models, the bootstrap, and empirical processes and their applications. The topics are organized from the central idea of approximation by limit experiments, one of the book's unifying themes that mainly entails the local approximation of the classical i.i.d. set up with smooth parameters by location experiments involving a single, normally distributed observation.
Country USA
Brand Cambridge University Press
Manufacturer Cambridge University Press
Binding Paperback
ItemPartNumber 14 b/w illus. 8 tables
ReleaseDate 2000-09-14
UnitCount 1
Format Illustrated
EANs 9780521784504

You might also like...

High-Dimensional Probability: An Introduction with Applications in Data Science (Cambridge Series in Statistical and Probabilistic Mathematics)

High-Dimensional Probability: An Introduction with Applications in Data Science (Cambridge Series in Statistical and Probabilistic Mathematics)

Testing Statistical Hypotheses (Springer Texts in Statistics)

Testing Statistical Hypotheses (Springer Texts in Statistics)

The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition (Springer Series in Statistics)

The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition (Springer Series in Statistics)

Causal Inference for Statistics, Social, and Biomedical Sciences: An Introduction

Causal Inference for Statistics, Social, and Biomedical Sciences: An Introduction

Bayesian Data Analysis (Chapman & Hall/CRC Texts in Statistical Science)

Bayesian Data Analysis (Chapman & Hall/CRC Texts in Statistical Science)

Fundamentals of Nonparametric Bayesian Inference (Cambridge Series in Statistical and Probabilistic Mathematics)

Fundamentals of Nonparametric Bayesian Inference (Cambridge Series in Statistical and Probabilistic Mathematics)

Probability: Theory and Examples (Cambridge Series in Statistical and Probabilistic Mathematics)

Probability: Theory and Examples (Cambridge Series in Statistical and Probabilistic Mathematics)

A Course in Large Sample Theory (Chapman & Hall/CRC Texts in Statistical Science)

A Course in Large Sample Theory (Chapman & Hall/CRC Texts in Statistical Science)

High-Dimensional Statistics: A Non-Asymptotic Viewpoint (Cambridge Series in Statistical and Probabilistic Mathematics)

High-Dimensional Statistics: A Non-Asymptotic Viewpoint (Cambridge Series in Statistical and Probabilistic Mathematics)

Computer Age Statistical Inference: Algorithms, Evidence, and Data Science (Institute of Mathematical Statistics Monographs)

Computer Age Statistical Inference: Algorithms, Evidence, and Data Science (Institute of Mathematical Statistics Monographs)