| 書目名稱 | Nonparametric and Semiparametric Models | | 編輯 | Wolfgang H?rdle,Axel Werwatz,Stefan Sperlich | | 視頻video | http://file.papertrans.cn/668/667838/667838.mp4 | | 叢書名稱 | Springer Series in Statistics | | 圖書封面 |  | | 描述 | .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 biom | | 出版日期 | Book 2004 | | 關(guān)鍵詞 | Additive Models; Density Estimation; Generalized Partial Linear Models; Nonparametric Models; Regression | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-642-17146-8 | | isbn_softcover | 978-3-642-62076-8 | | isbn_ebook | 978-3-642-17146-8Series ISSN 0172-7397 Series E-ISSN 2197-568X | | issn_series | 0172-7397 | | copyright | Springer-Verlag Berlin Heidelberg 2004 |
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