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Nonparametric estimation with aggregated data
- Source :
- IndraStra Global.
- Publication Year :
- 2002
-
Abstract
- We introduce a kernel-based estimator of the density function and regression function for data that have been grouped into family totals. We allow for a common intrafamily component but require that observations from different families be independent. We establish consistency and asymptotic normality for our procedures. As usual, the rates of convergence can be very slow depending on the behavior of the characteristic function at infinity. We investigate the practical performance of our method in a simple Monte Carlo experiment.
- Subjects :
- Economics and Econometrics
Characteristic function (probability theory)
Nonparametric statistics
Asymptotic distribution
Estimator
jel:C13
jel:C24
Probability density function
jel:C14
Nonparametric regression
Grouped data
Aggregated data
deconvolution
grouped data
kernel
nonparametric regression
Kernel (statistics)
Aggregated data, deconvolution, grouped data, kernel, nonparametric regression
jel:C1
Applied mathematics
HA Statistics
Social Sciences (miscellaneous)
Mathematics
Subjects
Details
- Language :
- English
- ISSN :
- 23813652
- Database :
- OpenAIRE
- Journal :
- IndraStra Global
- Accession number :
- edsair.doi.dedup.....817f950c79a0764aa8edc548af53d199