Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/769
Title: Comparing partial and truncated conglomerates from a concentration theoretic point of view
Authors: EGGHE, Leo 
ROUSSEAU, Ronald 
Issue Date: 2005
Publisher: Elsevier
Source: Mathematical and Computer Modelling, 41(2-3). p. 301-311
Abstract: When studying numerical properties of a population (technically: a conglomerate) it often happens that not all data are known. It might be that the total number of objects (persons) in the population is known, but that data on a number of them is missing. It even happens frequently that the total number of objects (N) is unknown. Referring to the population as ‘sources’ and to the property under investigation as ‘items’ or as ‘the production’, the whole dataset of this conglomerate can be represented as an N-vector. In this article N-vectors representing sources and their respective productions are studied from the point of view of concentration theory. Partial vectors (N is known, but data concerning the least productive sources are missing) and truncated vectors (N is unknown) are compared in two ways. First-order comparisons study vectors, while second-order comparisons study differences between vectors. In the case of first-order comparisons, it is shown that truncated vectors may be incomparable, while partial ones are always completely comparable. Similarly for second-order comparisons, partial vectors can be compared and yield a totally ordered double sequence, while truncated ones may be incomparable. Finally, we describe how to make second-order comparisons for vectors with a different number
Keywords: Truncation; Partial conglomerates; Generalized bibliographies; Concentration
Document URI: http://hdl.handle.net/1942/769
ISSN: 0895-7177
DOI: 10.1016/j.mcm.2003.08.009
ISI #: 000227914600012
Category: A1
Type: Journal Contribution
Validations: ecoom 2006
Appears in Collections:Research publications

Files in This Item:
File Description SizeFormat 
comparing 1.pdfPublished version605.97 kBAdobe PDFView/Open
Show full item record

SCOPUSTM   
Citations

4
checked on Sep 2, 2020

WEB OF SCIENCETM
Citations

3
checked on Apr 22, 2024

Page view(s)

76
checked on Sep 7, 2022

Download(s)

110
checked on Sep 7, 2022

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.