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Smoothing Methods in Statistics

, nonparametric regression estimation, categorical data smoothing, and applications of smoothing to other areas of statistics. It will thus be;

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Nonparametric Smoothing and Lack-of-Fit Tests

An exploration of the use of smoothing methods in testing the fit of parametric regression models. The book reviews many of the existing;

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Asymmetric Kernel Smoothing

This is the first book to provide an accessible and comprehensive introduction to a newly developed smoothing technique using asymmetric;

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Kernel Smoothing

Comprehensive theoretical overview of kernel smoothing methods with motivating examples Kernel smoothing is a flexible nonparametric curve;

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Institute of Mathematical Statistics Textbooks

Filtering and smoothing methods are used to produce an accurate estimate of the state of a time-varying system based on multiple;

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Institute of Mathematical Statistics Textbooks

Filtering and smoothing methods are used to produce an accurate estimate of the state of a time-varying system based on multiple;

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Elements of Statistical Computing

statistics. Included are discussions of numerical analysis, numerical integration, and smoothing. The author give special attention to floating;

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Econometric Society Monographs

Applied Nonparametric Regression is the first book to bring together in one place the techniques for regression curve smoothing involving;

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Cambridge Series in Statistical and Probabilistic Mathematics

series and forecasting, mixture models, survival analysis, Bayesian smoothing, and non-linear random effects models. The text includes a large;

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Cambridge Series in Statistical and Probabilistic Mathematics

series and forecasting, mixture models, survival analysis, Bayesian smoothing, and non-linear random effects models. The text includes a large;

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Nonparametric Models for Longitudinal Data

models and smoothing methods with longitudinal data. It covers methods, theories, and applications that are particularly useful for biomedical;

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The GETMe Mesh Smoothing Framework

Laplacian smoothing, with a high computational efficiency but possible low resulting mesh quality, to global optimization-based methods, resulting;

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The GETMe Mesh Smoothing Framework

Laplacian smoothing, with a high computational efficiency but possible low resulting mesh quality, to global optimization-based methods, resulting;

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Nonparametric Models for Longitudinal Data

models and smoothing methods with longitudinal data. It covers methods, theories, and applications that are particularly useful for biomedical;

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Recent Advances and Trends in Nonparametric Statistics

. Classical nonparametric procedures, such as function smoothing, suddenly lost their abstract flavour as they became practically implementable;

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Smoothing Splines

A general class of powerful and flexible modeling techniques, spline smoothing has attracted a great deal of research attention in recent;

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Smoothing Splines

A general class of powerful and flexible modeling techniques, spline smoothing has attracted a great deal of research attention in recent;

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Mathematical Statistics

well as applications of stochastic analysis in modern statistics, e.g., Kolmogorov-Smirnov testing, smoothing techniques, robustness and;

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Forecasting with Exponential Smoothing

Exponential smoothing methods have been around since the 1950s, and are still the most popular forecasting methods used in business and;

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Kernel Smoothing

Kernel smoothing refers to a general methodology for recovery of underlying structure in data sets.The basic principle is that local;

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Nonparametric Regression and Spline Smoothing

Provides a unified account of the most popular approaches to nonparametric regression smoothing. This edition contains discussions;

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Nonparametric Regression and Spline Smoothing

Provides a unified account of the most popular approaches to nonparametric regression smoothing. This edition contains discussions;

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Computational Statistics

is comprised of four main parts spanning the field: * Optimization * Integration and Simulation * Bootstrapping * Density Estimation and Smoothing;

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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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Nonparametric Regression and Generalized Linear Models

In recent years, there has been a great deal of interest and activity in the general area of nonparametric smoothing in statistics. This;

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Nonparametric Methods in Statistics with SAS Applications

Fisher exact tests. It then discusses smoothing techniques (loess and thin-plate splines) for classical nonparametric regression as well as;

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Nonparametric Methods In Statistics With Sas Applications

Fisher exact tests. It then discusses smoothing techniques (loess and thin-plate splines) for classical nonparametric regression as well as;

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