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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/3848

Title: Classification of growth-models based on growth-rates and its applications
Authors: EGGHE, Leo
RAO, Ravichandra
Issue Date: 1992
Citation: SCIENTOMETRICS, 25(1). p. 5-46
Abstract: In this paper, growth models are classified and characterised using two types of growth rates: from time t to t + 1 and from time t to 2t. They are interesting in themselves but can also be used for a quick prediction of the type of growth model that is valid in a particular case. These ideas are applied on 20 data sets collected by Wolfram, Chu and Lu. We determine (using the above classification as well as via nonlinear regression techniques) that the power model (with exponent > 1) is the best growth model for Sci-Tech online databases, but that Gompertz-S-shaped distribution is the best for social sciences and humanities online databases.
Notes: UNIV INSTELLING ANTWERP,B-2610 WILRIJK,BELGIUM. DRTC,BANGALORE 5600059,INDIA.EGGHE, L, LIMBURGS UNIV CENTRUM,UNIV CAMPUS,B-3590 DIEPENBEEK,BELGIUM.
URI: http://hdl.handle.net/1942/3848
DOI: 10.1007/BF02016845
ISI #: A1992JU16400001
ISSN: 0138-9130
Type: Journal Contribution
Appears in Collections: Research publications

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