Publisher description for Semiparametric regression / David Ruppert, M.P. Wand, R.J. Carroll.
Bibliographic record and links to related information available from the Library of Congress catalog
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Science abounds with problems where the data are noisy and the answer is not a straight line. Semiparametric regression analysis helps make sense of such data in application areas that include engineering, finance, medicine and public health. The book is geared towards researchers and professionals with little background in regression as well as statistically oriented scientists (biostatisticians, econometricians, quantitative social scientists, and epidemiologists) with knowledge of regression and the desire to begin using more flexible semiparametric models.
Library of Congress subject headings for this publication: Regression analysis, Nonparametric statistics