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Nonparametric and semiparametric models

By: Hardle, WolfgangContributor(s): Muller, Marlene | Sperlich, Stefan | Werwatz, AxelMaterial type: Text

TextSeries: Springer series in statisticsPublication details: Berlin ; New York : Springer, ©2004Description: xxvii, 299 pagesISBN: 9783540207221; 3540207228 Subject(s): Nonparametric statistics | Mathematical modelsDDC classification: 519.5

Contents:

1. Introduction -- Part I. Nonparametric models -- 2. Histogram -- 3. Nonparametric density estimation -- 4. Nonparametric regression -- Part II. Semiparametric models -- 5. Semiparametric and generalized regression models -- 6. Single index models -- 7. Generalized partial linear models -- 8. Additive models and marginal effects -- 9. Generalized additive models.

Summary: It naturally splits into two parts: The first part is intended for undergraduate students majoring in mathematics, statistics, econometrics or biometrics whereas the second part is intended to be used by master and PhD students or researchers.

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Holdings
Item type	Current library	Collection	Call number	Status	Date due	Barcode	Item holds
Permanent Reference	Main Library Permanent Reference	Reference	519.5 NON (Browse shelf(Opens below))	Not for loan		012138
Reference Books	Main Library Reference	Reference	519.5 NON (Browse shelf(Opens below))	Available		011303

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Previous	519.5 MIN Elements of statistical reasoning	519.5 NEL The analysis of means : a graphical method for comparing means, rates and proportions	519.5 NEL The analysis of means : a graphical method for comparing means, rates and proportions	519.5 NON Nonparametric and semiparametric models	519.5 OWE Statistics	519.5 OWE Statistics	519.5 PAG Understanding statistics in the behavioral science	Next

Bibliography & Index

1. Introduction --
Part I. Nonparametric models --
2. Histogram --
3. Nonparametric density estimation --
4. Nonparametric regression --
Part II. Semiparametric models --
5. Semiparametric and generalized regression models --
6. Single index models --
7. Generalized partial linear models --
8. Additive models and marginal effects --
9. Generalized additive models.

It naturally splits into two parts: The first part is intended for undergraduate students majoring in mathematics, statistics, econometrics or biometrics whereas the second part is intended to be used by master and PhD students or researchers.

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