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Statistique mathematique --- Moindres carres --- Curve fitting --- Methodes numeriques
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Analyse de régression --- Regression analysis. --- Curve fitting
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Numerical calculations. --- Mathematical statistics. --- Error analysis (Mathematics). --- Curve fitting.
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Least squares. --- Curve fitting --- Moindres carrés --- Courbes empiriques
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The book describes the use of smoothing techniques in statistics, including both density estimation and nonparametric regression. Considerable advances in research in this area have been made in recent years. The aim of this text is to describe a variety of ways in which these methods can be applied to practical problems in statistics. The role of smoothing techniques in exploring data graphically is emphasised, but the use of nonparametric curves in drawing conclusions from data, as an extension of more standard parametric models, is also a major focus of the book. Examples are drawn from a wide range of applications. The book is intended for those who seek an introduction to the area, with an emphasis on applications rather than on detailed theory. It is therefore expected that the book will benefit those attending courses at an advanced undergraduate, or postgraduate, level, as well as researchers, both from statistics and from other disciplines, who wish to learn about and apply these techniques in practical data analysis. The text makes extensive reference to S-Plus, as a computing environment in which examples can be explored.; S-Plus functions and example scripts are provided to implement many of the techniques described. These parts are, however, clearly separate from the main body of text, and can therefore easily be skipped by readers not interested in S-Plus.
Smoothing (Statistics) --- Mathematics --- Physical Sciences & Mathematics --- Mathematical Statistics --- Curve fitting --- Graduation (Statistics) --- Roundoff errors --- Statistics
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Distribution (Probability theory) --- Speed. --- Measurement --- Measuring instruments --- Error analysis --- Calibrating --- Curve fitting
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Statistique mathématique --- Mathematical statistics. --- Statistique mathematique --- Curve fitting --- Controle de qualite
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Here is a clear exposition of nonparametric smoothing methods for statisticians. The focus is applied rather than theoretical, with a large number of illustrations from different disciplines.
Mathematical statistics --- Smoothing (Statistics) --- Smoothing (Statistics). --- Basic Sciences. Statistics --- Experimental Design. --- 519.5 --- Curve fitting --- Graduation (Statistics) --- Roundoff errors --- Statistics
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Creating More Effective Graphs gives you the basic knowledge and techniques required to choose and create appropriate graphs for a broad range of applications. Using real-world examples everyone can relate to, the author highlights some of today's most effective methods. In clear, concise language, the author answers such common questions as: What constitutes an effective graph for communicating data? How do I choose the type of graph that is best for my data? How do I recognize a misleading graph? Whether you're a novice at graphing or already use graphs in your work but want to improve them, Creating More Effective Graphs will help you develop the kind of clear, accurate, and well-designed graphs to allow your data to be understood.
effectiviteit --- Mathematical statistics --- grafieken --- wiskundige statistiek --- Statistics --- Graphic methods. --- Diagrams, Statistical --- Statistical diagrams --- Curve fitting --- Graphic methods
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Methods of kernel estimates represent one of the most effective nonparametric smoothing techniques. These methods are simple to understand and they possess very good statistical properties. This book provides a concise and comprehensive overview of statistical theory and in addition, emphasis is given to the implementation of presented methods in Matlab. All created programs are included in a special toolbox which is an integral part of the book. This toolbox contains many Matlab scripts useful for kernel smoothing of density, cumulative distribution function, regression function, hazard funct
Smoothing (Statistics) --- Kernel functions. --- Functions, Kernel --- Functions of complex variables --- Geometric function theory --- Curve fitting --- Graduation (Statistics) --- Roundoff errors --- Statistics