Local Regression and Likelihood
Buch in deiner Nähe kaufen
Beschreibung
Separation of signal from noise is the most fundamental problem in data analysis, and arises in many fields, for example, signal processing, econometrics, acturial science, and geostatistics. This book introduces the local regression method in univariate and multivariate settings, and extensions to local likelihood and density estimation. Basic theoretical results and diagnostic tools such as cross validation are introduced along the way. Examples illustrate the implementation of the methods using the LOCFIT software.
Smoothing methods play an important role in many areas of statistics. This book explains how to implement these methods in several popular statistical programs including S-PLUS.
Autor*in
Catherine Loader
Themen in »Local Regression and Likelihood«
Density Estimation Fitting Likelihood Local Likelihood Local Regression Variance best fit data analysis statistics quantitative finance