Nonparametric and Semiparametric Models:
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Berlin, Heidelberg
Springer Berlin Heidelberg
2004
|
| Schriftenreihe: | Springer Series in Statistics
|
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Beschreibung: | The concept of nonparametric smoothing is a central idea in statistics that aims to simultaneously estimate and modes the underlying structure. The book considers high dimensional objects, as density functions and regression. The semiparametric modeling technique compromises the two aims, flexibility and simplicity of statistical procedures, by introducing partial parametric components. These components allow to match structural conditions like e.g. linearity in some variables and may be used to model the influence of discrete variables. The aim of this monograph is to present the statistical and mathematical principles of smoothing with a focus on applicable techniques. The necessary mathematical treatment is easily understandable and a wide variety of interactive smoothing examples are given. The book does naturally split into two parts: Nonparametric models (histogram, kernel density estimation, nonparametric regression) and semiparametric models (generalized regression, single index models, generalized partial linear models, additive and generalized additive models). 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. The material is easy to accomplish since the e-book character of the text gives a maximum of flexibility in learning (and teaching) intensity |
| Beschreibung: | 1 Online-Ressource (XXVII, 300 p) |
| ISBN: | 9783642171468 9783642620768 |
| ISSN: | 0172-7397 |
| DOI: | 10.1007/978-3-642-17146-8 |
Internformat
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Datensatz im Suchindex
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| doi_str_mv | 10.1007/978-3-642-17146-8 |
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| id | DE-604.BV042422458 |
| illustrated | Not Illustrated |
| indexdate | 2024-07-10T01:21:11Z |
| institution | BVB |
| isbn | 9783642171468 9783642620768 |
| issn | 0172-7397 |
| language | English |
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| spelling | Härdle, Wolfgang Verfasser aut Nonparametric and Semiparametric Models by Wolfgang Härdle, Axel Werwatz, Marlene Müller, Stefan Sperlich Berlin, Heidelberg Springer Berlin Heidelberg 2004 1 Online-Ressource (XXVII, 300 p) txt rdacontent c rdamedia cr rdacarrier Springer Series in Statistics 0172-7397 The concept of nonparametric smoothing is a central idea in statistics that aims to simultaneously estimate and modes the underlying structure. The book considers high dimensional objects, as density functions and regression. The semiparametric modeling technique compromises the two aims, flexibility and simplicity of statistical procedures, by introducing partial parametric components. These components allow to match structural conditions like e.g. linearity in some variables and may be used to model the influence of discrete variables. The aim of this monograph is to present the statistical and mathematical principles of smoothing with a focus on applicable techniques. The necessary mathematical treatment is easily understandable and a wide variety of interactive smoothing examples are given. The book does naturally split into two parts: Nonparametric models (histogram, kernel density estimation, nonparametric regression) and semiparametric models (generalized regression, single index models, generalized partial linear models, additive and generalized additive models). 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. The material is easy to accomplish since the e-book character of the text gives a maximum of flexibility in learning (and teaching) intensity Statistics Mathematical statistics Economics / Statistics Econometrics Statistics for Business/Economics/Mathematical Finance/Insurance Statistical Theory and Methods Statistik Wirtschaft Semiparametrisches Modell (DE-588)4232479-8 gnd rswk-swf Nichtparametrisches Modell (DE-588)4434654-2 gnd rswk-swf Semiparametrisches Modell (DE-588)4232479-8 s 1\p DE-604 Nichtparametrisches Modell (DE-588)4434654-2 s 2\p DE-604 Werwatz, Axel Sonstige oth Müller, Marlene Sonstige oth Sperlich, Stefan Sonstige oth https://doi.org/10.1007/978-3-642-17146-8 Verlag Volltext 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk 2\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Härdle, Wolfgang Nonparametric and Semiparametric Models Statistics Mathematical statistics Economics / Statistics Econometrics Statistics for Business/Economics/Mathematical Finance/Insurance Statistical Theory and Methods Statistik Wirtschaft Semiparametrisches Modell (DE-588)4232479-8 gnd Nichtparametrisches Modell (DE-588)4434654-2 gnd |
| subject_GND | (DE-588)4232479-8 (DE-588)4434654-2 |
| title | Nonparametric and Semiparametric Models |
| title_auth | Nonparametric and Semiparametric Models |
| title_exact_search | Nonparametric and Semiparametric Models |
| title_full | Nonparametric and Semiparametric Models by Wolfgang Härdle, Axel Werwatz, Marlene Müller, Stefan Sperlich |
| title_fullStr | Nonparametric and Semiparametric Models by Wolfgang Härdle, Axel Werwatz, Marlene Müller, Stefan Sperlich |
| title_full_unstemmed | Nonparametric and Semiparametric Models by Wolfgang Härdle, Axel Werwatz, Marlene Müller, Stefan Sperlich |
| title_short | Nonparametric and Semiparametric Models |
| title_sort | nonparametric and semiparametric models |
| topic | Statistics Mathematical statistics Economics / Statistics Econometrics Statistics for Business/Economics/Mathematical Finance/Insurance Statistical Theory and Methods Statistik Wirtschaft Semiparametrisches Modell (DE-588)4232479-8 gnd Nichtparametrisches Modell (DE-588)4434654-2 gnd |
| topic_facet | Statistics Mathematical statistics Economics / Statistics Econometrics Statistics for Business/Economics/Mathematical Finance/Insurance Statistical Theory and Methods Statistik Wirtschaft Semiparametrisches Modell Nichtparametrisches Modell |
| url | https://doi.org/10.1007/978-3-642-17146-8 |
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