Quantile Estimation Using the Maximum Transformation, Stochastic Approximation and the Jackknife.
Abstract
The rate of convergence of the expected value of quantile estimates using a stochastic approximation with the maximum transformation is evaluated. The analysis is performed using linear regression techniques on computer simulation results for quantile estimates of the unit exponential distribution. Included is a discussion of the use of the jackknife technique to reduce the bias of the stochastic approximation quantile estimates. Simulation results for the 2-fold jackknife for the m sup(-.5) term are tabulated. The main conclusion of the analysis is that the lowest order term in the expression for the expected value of the estimate as a function of sample size decreases as m sup(-.25). (Author)
Document Details
- Document Type
- Technical Report
- Publication Date
- Mar 01, 1973
- Accession Number
- AD0761763
Entities
People
- Tadashi Glenn Yuguchi
Organizations
- Naval Postgraduate School