A Weak Invariance Principle with Applications to Domains of Attraction,
Abstract
An elementary probabilistic argument is given which establishes a 'weak invariance principle' which in turn implies the sufficiency of the classical assumptions associated with the weak convergence of normed sums to stable laws. The argument, which uses quantile functions (the inverses of distribution functions), exploits the fact that two random variables X = F sup(-1)(U) and Y = G sup(-1)(U) are, in a useful sense, close together when F and G are, in a certain sense, close together. Here U denotes a uniform variable on (0,1). Byproducts of the research are two alternative characterizations for a random variable being in the domain of partial attraction to a normal law and some results concerning the study of domains of partial attraction.
Document Details
- Document Type
- Technical Report
- Publication Date
- Nov 01, 1975
- Accession Number
- ADA023297
Entities
People
- Gordon Simons
- William Stout
Organizations
- University of North Carolina at Chapel Hill