On methods of statistical inference with the use of the empirical characteristic function

Abstract

The subject of the present dissertation is the analytic and numerical investigation of certain procedures of Statistical Inference which use the empirical characteristic function (ecf). In Chapter I we introduce the characteristic function and the ecf and go through some of their important properties. We then provide an intoduction to the history of the applications of the ecf in Statistical Inference and a quick description of the original material in this dissertation which is included in Chapters II to IV. Chapter II contains an analytic and numerical investigation of the behavior of an estimator in which the polar coordinates of the ecf are calculated at a finite number of points. Asymptotic normality is proved and the efficiency of the proposed estimator is investigated based on asymptotic results and results from finite samples. These results pertain to some well known symmetric models which are useful in applied research and for which the standard methods of estimation are not e ...
show more

All items in National Archive of Phd theses are protected by copyright.

DOI
10.12681/eadd/1494
Handle URL
http://hdl.handle.net/10442/hedi/1494
ND
1494
Alternative title
Επί μεθόδων στατιστικής συπερασματολογίας με χρήση της εμπειρικής χαρακτηριστικής συνάρτησης
Author
Meintanis, Simos (Father's name: G.)
Date
1990
Degree Grantor
University of Patras
Committee members
Κουτρουβέλης Ιωάννης
Μάρκελλος Βασίλειος
Σύψας Παναγιώτης
Κακούλος Θεόφιλος
Παπαγεωργίου Χαράλαμπος
Discipline
Natural SciencesMathematics
Keywords
Characteristic function; Empirical characteristic function; Goodness of fit tests; Non-parametric estimation
Country
Greece
Language
Greek
Description
212 σ.
Usage statistics
VIEWS
Concern the unique Ph.D. Thesis' views for the period 07/2018 - 07/2023.
Source: Google Analytics.
ONLINE READER
Concern the online reader's opening for the period 07/2018 - 07/2023.
Source: Google Analytics.
DOWNLOADS
Concern all downloads of this Ph.D. Thesis' digital file.
Source: National Archive of Ph.D. Theses.
USERS
Concern all registered users of National Archive of Ph.D. Theses who have interacted with this Ph.D. Thesis. Mostly, it concerns downloads.
Source: National Archive of Ph.D. Theses.
Related items (based on users' visits)