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The Art of Semiparametrics

Contributor(s): Sperlich, Stefan [editor.] | Härdle, Wolfgang [editor.] | Aydınlı, Gökhan [editor.] | SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Contributions to Statistics: Publisher: Heidelberg : Physica-Verlag HD, 2006.Description: VIII, 178 p. 33 illus. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783790817010.Subject(s): Mathematics | Probabilities | Statistics | Econometrics | Mathematics | Probability Theory and Stochastic Processes | Statistical Theory and Methods | Statistics for Business/Economics/Mathematical Finance/Insurance | Statistics and Computing/Statistics Programs | EconometricsDDC classification: 519.2 Online resources: Click here to access online
Contents:
Asymptotic Theory for M-Estimators of Boundaries -- A Simple Deconvolving Kernel Density Estimator when Noise Is Gaussian -- Nonparametric Volatility Estimation on the Real Line from Low Frequency Data -- Linear Regression Models for Functional Data -- Penalized Binary Regression as Statistical Learning Tool for Microarray Analysis -- A Relaxed Iterative Projection Algorithm for Rank-Deficient Regression Problems -- About Sense and Nonsense of Non- and Semiparametric Analysis in Applied Economics -- Functional Nonparametric Statistics in Action -- Productivity Effects of IT-Outsourcing: Semiparametric Evidence for German Companies -- Nonparametric and Semiparametric Estimation of Additive Models with Both Discrete and Continuous Variables under Dependence.
In: Springer eBooksSummary: This selection of articles has emerged from different works presented at the conference "The Art of Semiparametrics" celebrated in 2003 in Berlin. The idea was to bring together junior and senior researchers but also practitioners working on semiparametric statistics in rather different fields. The meeting succeeded in welcoming a group that presents a broad range of areas where research on, respectively with, semiparametric methods is going on. It contains mathematical statistics, econometrics, finance, business statistics, etc. and thus combines theoretical contributions with more applied and partly even empirical studies. Although each article represents an original contribution to its own field, they all are written in a self-contained way to be read also by non-experts of the particular topic. This volume therefore offers a collection of individual works that together show the actual large spectrum of semiparametric statistics.
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Asymptotic Theory for M-Estimators of Boundaries -- A Simple Deconvolving Kernel Density Estimator when Noise Is Gaussian -- Nonparametric Volatility Estimation on the Real Line from Low Frequency Data -- Linear Regression Models for Functional Data -- Penalized Binary Regression as Statistical Learning Tool for Microarray Analysis -- A Relaxed Iterative Projection Algorithm for Rank-Deficient Regression Problems -- About Sense and Nonsense of Non- and Semiparametric Analysis in Applied Economics -- Functional Nonparametric Statistics in Action -- Productivity Effects of IT-Outsourcing: Semiparametric Evidence for German Companies -- Nonparametric and Semiparametric Estimation of Additive Models with Both Discrete and Continuous Variables under Dependence.

This selection of articles has emerged from different works presented at the conference "The Art of Semiparametrics" celebrated in 2003 in Berlin. The idea was to bring together junior and senior researchers but also practitioners working on semiparametric statistics in rather different fields. The meeting succeeded in welcoming a group that presents a broad range of areas where research on, respectively with, semiparametric methods is going on. It contains mathematical statistics, econometrics, finance, business statistics, etc. and thus combines theoretical contributions with more applied and partly even empirical studies. Although each article represents an original contribution to its own field, they all are written in a self-contained way to be read also by non-experts of the particular topic. This volume therefore offers a collection of individual works that together show the actual large spectrum of semiparametric statistics.

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