Weighted nonparametric tail estimation procedures
Technical Report
·
OSTI ID:5689565
This paper investigates procedures for univariate nonparametric estimation of tail probabilities. Extrapolated values for tail probabilities beyond the data are also obtained based on the shape of the density in the tail. Several estimators which use exponential weighting are described. These are compared in a Monte Carlo study to nonweighted estimators, to the empirical cdf, to an integrated kernel, to a Fourier series estimate, to a penalized likelihood estimate and a maximum likelihood estimate. Selected weighted estimators are shown to compare favorably to many of these standard estimators for the sampling distributions investigated.
- Research Organization:
- Pacific Northwest Lab., Richland, WA (USA)
- DOE Contract Number:
- AC06-76RL01830
- OSTI ID:
- 5689565
- Report Number(s):
- PNL-SA-11167; ON: DE83017870
- Country of Publication:
- United States
- Language:
- English
Similar Records
Estimating tail probabilities
Nonparametric conditional estimation
Quasar Identification Using Multivariate Probability Density Estimated from Nonparametric Conditional Probabilities
Technical Report
·
Tue Nov 30 23:00:00 EST 1982
·
OSTI ID:6568797
Nonparametric conditional estimation
Technical Report
·
Wed Dec 31 23:00:00 EST 1986
·
OSTI ID:6536801
Quasar Identification Using Multivariate Probability Density Estimated from Nonparametric Conditional Probabilities
Journal Article
·
Tue Dec 27 23:00:00 EST 2022
· Mathematics
·
OSTI ID:2425264