☰

Probability & Statistics

Empirical Processes in M-Estimation (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 6)

R 2,604

or 4 x payments of R651.00 with Payflex

Payflex

Availability: Currently in Stock

Delivery: 10-20 working days

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.

Empirical Processes in M-Estimation (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 6)

The theory of empirical processes provides valuable tools for the development of asymptotic theory in (nonparametric) statistical models, and makes it possible to give a unified treatment of various models. This book reveals the relation between the asymptotic behavior of M-estimators and the complexity of parameter space, using entropy as a measure of complexity, presenting tools and methods to analyze nonparametric, and in some cases, semiparametric methods. Graduate students and professionals in statistics, as well as those interested in applications, e.g. to econometrics, medical statistics, etc., will welcome this treatment.
Country USA
Brand Cambridge University Press
Manufacturer Cambridge University Press
Binding Paperback
ReleaseDate 2009-11-19
UnitCount 1
Format Illustrated
EANs 9780521123259

You might also like...

Asymptotic Statistics (Cambridge Series in Statistical and Probabilistic Mathematics)

Asymptotic Statistics (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)

Statistics for High-Dimensional Data: Methods, Theory and Applications (Springer Series in Statistics)

Statistics for High-Dimensional Data: Methods, Theory and Applications (Springer Series in Statistics)

Convergence Of Probability Measures 2Ed (Pb 2014)

Convergence Of Probability Measures 2Ed (Pb 2014)

Weak Convergence and Empirical Processes: With Applications to Statistics (Springer Series in Statistics)

Weak Convergence and Empirical Processes: With Applications to Statistics (Springer Series in Statistics)

Advanced R (Chapman & Hall/CRC The R Series)

Advanced R (Chapman & Hall/CRC The R Series)

Large-Scale Inference: Empirical Bayes Methods for Estimation, Testing, and Prediction (Institute of Mathematical Statistics Monographs)

Large-Scale Inference: Empirical Bayes Methods for Estimation, Testing, and Prediction (Institute of Mathematical Statistics Monographs)

Deep Learning (Adaptive Computation and Machine Learning series)

Deep Learning (Adaptive Computation and Machine Learning series)

Concentration Inequalities: A Nonasymptotic Theory of Independence

Concentration Inequalities: A Nonasymptotic Theory of Independence