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Bagging of density estimators
- Source :
- Computational Statistics. 34:1849-1869
- Publication Year :
- 2019
- Publisher :
- Springer Science and Business Media LLC, 2019.
-
Abstract
- In this work we give new density estimators by averaging classical density estimators such as the histogram, the frequency polygon and the kernel density estimators obtained over different bootstrap samples of the original data. We prove the L 2-consistency of these new estimators and compare them to several similar approaches by extensive simulations. Based on them, we give also a way to construct non parametric pointwise confidence intervals for the target density.
- Subjects :
- FOS: Computer and information sciences
Statistics and Probability
Pointwise
05 social sciences
Kernel density estimation
Nonparametric statistics
Estimator
Density estimation
01 natural sciences
Confidence interval
Methodology (stat.ME)
010104 statistics & probability
Computational Mathematics
Histogram
0502 economics and business
Polygon
Applied mathematics
0101 mathematics
Statistics, Probability and Uncertainty
Statistics - Methodology
050205 econometrics
Mathematics
Subjects
Details
- ISSN :
- 16139658 and 09434062
- Volume :
- 34
- Database :
- OpenAIRE
- Journal :
- Computational Statistics
- Accession number :
- edsair.doi.dedup.....4d0c338fcaf90432db72bc26a1432694