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U Statistics Mm Estimators and Resampling

of U-statistics and Mm-estimators and develops their asymptotic properties. It also provides an elementary introduction to resampling, particularly in the;

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U-Statistics

In 1946 Paul Halmos studied unbiased estimators of minimum variance, and planted the seed from which the subject matter of the present;

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U-Statistics: Theory and Practice

In 1946 Paul Halmos studied unbiased estimators of minimum variance, and planted the seed from which the subject matter of the present;

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Introductory Statistics and Analytics

, and the bootstrap A uniquely developed presentation of key statistical topics, Introductory Statistics and Analytics: A Resampling Perspective;

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Mathematical Statistics with Resampling and R

Resampling helps students understand the meaning of sampling distributions, sampling variability, P-values, hypothesis tests, and confidence;

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Statistics is Easy!

distribution to the data (typically, the normal distribution) and derive results under that assumption. Unfortunately, in real life, one cannot;

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Statistics Is Easy!

distribution to the data (typically, the normal distribution) and derive results under that assumption. Unfortunately, in real life, one cannot;

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Computational Statistics in the Earth Sciences

sciences data using MATLAB. The book is organized to introduce the underlying concepts, and then extends these to the data, covering methods that;

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Non-Standard Parametric Statistical Inference

where the problem is non-standard when parameter estimates behave unusually, and (ii) the use of parametric bootstrap resampling methods;

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Random Circulant Matrices

Circulant matrices have been around for a long time and have been extensively used in many scientific areas. This book studies the;

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Random Circulant Matrices

Circulant matrices have been around for a long time and have been extensively used in many scientific areas. This book studies the;

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Probability With a View Towards Statistics, Volume II

Volume II of this two-volume text and reference work concentrates on the applications of probability theory to statistics, e.g., the art;

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An introduction to mathematical statistics

Statistics is the science that focuses on drawing conclusions from data, by modeling and analyzing the data using probabilistic models;

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An introduction to mathematical statistics

Statistics is the science that focuses on drawing conclusions from data, by modeling and analyzing the data using probabilistic models;

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Introductory Biostatistics For The Health Sciences

Accessible to medicine- and/or public policy-related audiences, as well as most statisticians. Emphasis on outliers is discussed by way;

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Computational Statistics

properties of estimators and test statistics. This book describes computationally intensive statistical methods in a unified presentation;

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Computational Statistics

properties of estimators and test statistics. This book describes computationally intensive statistical methods in a unified presentation;

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Statistical Theory and Inference

This text is for a one semester graduate course in statistical theory and covers minimal and complete sufficient statistics, maximum;

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Recent Advances and Trends in Nonparametric Statistics

. In addition, many previously unthinkable possibilities became mainstream; prime examples include the bootstrap and resampling methods, wavelets and;

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Instrumental Variables

Recent advances in establishing the nature and scope of estimators in econometrics have shed more light on the importance of instrumental;

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Statistical Tests Of Nonparametric Hypotheses

-Pearson and LeCam's theories of optimal tests, the theories of empirical processes and kernel estimators with extensions of their applications to;

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Introduction To Statistics Through Resam

Written in a highly accessible style, Introduction to Statistics through Resampling Methods and R, Second Edition guides students in the;

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New Developments in Applied Statistics

exponential distribution; inference and prediction for a generalised logistics distribution; minimum perpendicular distance squared method estimation;

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Econometric Modelling with Time Series

This book provides a general framework for specifying, estimating and testing time series econometric models. Special emphasis is given to;

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Econometric Modelling with Time Series

This book provides a general framework for specifying, estimating and testing time series econometric models. Special emphasis is given to;

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From Statistics to Mathematical Finance

experts in statistics, stochastic processes, mathematical finance and insurance. The individual chapters cover a wide variety of topics ranging;

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Smoothing of Multivariate Data

An applied treatment of the key methods and state-of-the-art tools for visualizing and understanding statistical data Smoothing;

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