Multivariate Density Estimation: Theory, Practice, and VisualizationJohn Wiley & Sons, 25 sept 2009 - 336 páginas Written to convey an intuitive feel for both theory and practice, its main objective is to illustrate what a powerful tool density estimation can be when used not only with univariate and bivariate data but also in the higher dimensions of trivariate and quadrivariate information. Major concepts are presented in the context of a histogram in order to simplify the treatment of advanced estimators. Features 12 four-color plates, numerous graphic illustrations as well as a multitude of problems and solutions. |
Otras ediciones - Ver todo
Multivariate Density Estimation: Theory, Practice, and Visualization David W. Scott Vista previa restringida - 1992 |
Multivariate Density Estimation: Theory, Practice, and Visualization David W. Scott No hay ninguna vista previa disponible - 2009 |
Términos y frases comunes
adaptive additive algorithm AMISE Analysis appear applied approach approximation asymptotic average bandwidth bias bins bivariate bootstrap boundary choice clusters compared computed conditional Consider constructed contour coordinates corresponding criterion curve defined density estimate density function derivative diagrams dimensions displayed equal Equation equivalent error examination example fact factor Figure first fixed follows frequency polygon function given gives histogram increases integrated interesting interval kernel estimate kernel regression linear matrix mean mesh methods minimizer MISE mode multivariate nonparametric Normal observed optimal origin oversmoothed plot points possible practical probability problem projection proposed random ratio reference region regression relative respectively result roughness rule sample scale Scott shown shows similar simple smoothing parameter solution squared Statistical structure suggests surface Table Theorem transformation true values variables variance visualization weights width