On a Unification of Bias Reduction and Numerical Approximation.
Abstract
In this paper it is shown that the problem of numerical approximation and bias reduction are basically the same problem and that many of the classical numerical methods are equivalent to the so-called jackknife method. In particular it is shown that Simpson's rule, Romberg integration, Newton-Cotes methods, Lagrange interpolation, the epsilon-algorithm, G-transforms, and others are simply special cases of the generalized jackknife. These observations are then used to obtain a new consistent estimator for the spectral density function. (Author)
Document Details
- Document Type
- Technical Report
- Publication Date
- Jul 01, 1974
- Accession Number
- AD0783719
Entities
People
- H. L. Gray
Organizations
- Southern Methodist University