Statistical inference on the h-index with an application to top-scientist performance |
| |
| Authors: | A Baccini L Barabesi M Marcheselli L Pratelli |
| |
| Institution: | 1. Department of Economics and Statistics, University of Siena, P.zza S.Francesco 7, 53100 Siena, Italy;2. Naval Academy, viale Italia 72, 57100 Leghorn, Italy;1. School of Business Administration, Federal University of Rio Grande do Sul, Porto Alegre, R.S., 90010-460, Brazil;2. Prometeo Researcher, Facultad de Ciencias Económicas y Administrativas, University of Cuenca, Ecuador;3. Graduate Program in Economics, Federal University of Santa Catarina, Florianopolis, S.C., 88049-970, Brazil;1. University of Munich, Germany;2. Ifo Institute for Economic Research at the University of Munich, Poschingerstr. 5, 81679 Munich, Germany;1. Departamento de Biblioteconomía y Documentación, Universidad Carlos III, SCImago Research Group, Spain;2. Departamento de Economía, Universidad Carlos III, Spain;1. Division for Science and Innovation Studies, Administrative Headquarters of the Max Planck Society, Hofgartenstr. 8, 80539 Munich, Germany;2. Max Planck Institute for Solid State Research, Heisenbergstr. 1, 70569 Stuttgart, Germany |
| |
| Abstract: | Despite the huge amount of literature concerning the h-index, few papers have been devoted to its statistical analysis when a probabilistic distribution is assumed for citation counts. The present contribution mainly aims to divulge the inferential techniques recently introduced by Pratelli et al. (2012), by explaining the details for proper point and set estimation of the theoretical h-index. Moreover, some new achievements on simultaneous inference – addressed to produce suitable scholar comparisons – are carried out. Finally, the analysis of the citation dataset for the Nobel Laureates (in the last five years) and for the Fields medallists (from 2002 onward) is considered in order to exemplify the theoretical issues. |
| |
| Keywords: | |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
