Nonparametric and semiparametric models

By: Hardle, WolfgangContributor(s): Muller, Marlene | Sperlich, Stefan | Werwatz, AxelMaterial type: TextTextSeries: 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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Permanent Reference Permanent Reference Pampaimadu
Permanent Reference 		Reference 519.5 NON (Browse shelf(Opens below)) Not for loan 012138
Reference Books Reference Books Pampaimadu
Reference 		Reference 519.5 NON (Browse shelf(Opens below)) Available 011303
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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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