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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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Practical Smoothing

This is a practical guide to P-splines, a simple, flexible and powerful tool for smoothing. P-splines combine regression on B-splines with;

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Econometric Society Monographs

focuses on the applications and practical problems of two central aspects of curve smoothing: the choice of smoothing parameters and the;

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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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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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Theory and Principles of Smoothing, Filtering and Prediction

A descriptive account based on the theory as well as principles of smoothing, filtering and prediction techniques has been presented;

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Institute of Mathematical Statistics Textbooks

Bayesian parameter estimation methods can be combined with state-of-the-art filtering and smoothing algorithms. The book's practical and;

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Institute of Mathematical Statistics Textbooks

Bayesian parameter estimation methods can be combined with state-of-the-art filtering and smoothing algorithms. The book's practical 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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Smoothing . KONSTANTIN, CD

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Vibration Reduction for Flexible Structures by Smoothing Commands

This book described vibration reduction for flexible structures by the command smoothing techniques. The Command smoothing technique is a;

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Flexible Regression and Smoothing

. In particular, the GAMLSS statistical framework enables flexible regression and smoothing models to be fitted to the data. The GAMLSS model assumes that;

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Flexible Regression and Smoothing

. In particular, the GAMLSS statistical framework enables flexible regression and smoothing models to be fitted to the data. The GAMLSS model assumes that;

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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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Smoothing, Filtering and Prediction

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Smoothing, Filtering and Prediction

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New Perspectives of Profit Smoothing

of profit smoothing, implemented by management, which aims to maintain a constant flow of profit over time. On an operational level, the phenomenon;

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Production Smoothing and Organizational Design

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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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Smoothing 3D prints from ABS using acetone vapors

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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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Smoothing of Multivariate Data

environment. Combining mathematical analysis with practical implementations, Smoothing of Multivariate Data is an excellent book for courses;

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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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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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