An Introduction to the Advanced Theory and Practice of Nonparametric Econometrics: A Replicable Approach Using R
(Sprache: Englisch)
Provides theory, open source R implementations, and the latest tools for reproducible nonparametric econometric research.
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Klappentext zu „An Introduction to the Advanced Theory and Practice of Nonparametric Econometrics: A Replicable Approach Using R “
Provides theory, open source R implementations, and the latest tools for reproducible nonparametric econometric research.
Inhaltsverzeichnis zu „An Introduction to the Advanced Theory and Practice of Nonparametric Econometrics: A Replicable Approach Using R “
Part I. Probability Functions, Probability Density Functions, and their Cumulative Counterparts: 1. Discrete probability and cumulative probability functions; 2. Continuous density and cumulative distribution functions; 3. Mixed-data probability density and cumulative distribution functions; 4. Conditional probability density and cumulative distribution functions; Part II. Conditional Moment Functions and Related Statistical Objects: 5. Conditional moment functions; 6. Conditional mean function estimation; 7. Conditional mean function estimation with endogenous predictors; 8. Semiparametric conditional mean function estimation; 9. Conditional variance function estimation; Part III. Appendices: A. Large and small orders of magnitude and probability; B. R, RStudio, TeX and Git; C. Computational considerations; D. R Markdown for assignments; E. Practicum.
Bibliographische Angaben
- Autor: Jeffrey S. Racine
- 340 Seiten, Maße: 15 x 21 cm, Gebunden, Englisch
- Verlag: CAMBRIDGE UNIV PR
- ISBN-10: 1108483402
- ISBN-13: 9781108483407
- Erscheinungsdatum: 31.03.2019
Sprache:
Englisch
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