Theory and practise of the g-index

Egghe, Leo

doi:10.1007/s11192-006-0144-7

Cited by 1,853 publications

(1,358 citation statements)

References 9 publications

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“…Another important impact indices and methods are planned to investigate in the near future, e.g. g-index (Egghe, 2006), highly cited papers (Aksnes, 2003;Aksnes & Taxt, 2004), percentile distribution of publications by citation Leydesdorff & Opthof, 2011).…”

Section: Resultsmentioning

confidence: 99%

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Would it be possible to increase the Hirsch-index, π-index or CDS-index by increasing the number of publications or citations only by unity?

Vinkler

2013

Journal of Informetrics

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The aim of the study is to explore the effects of the increase in the number of publications or citations on several impact indicators by a single journal paper or citation. The possible change of the h-index, A-index, R-index, -index, -rate, Journal Paper Citedness (JPC), and Citation Distribution Score (CDS) is followed by models. Particular attention is given to the increase of the indices by a single plus citation. The results obtained by the "Successively Built-up Indicator" model show that with increasing number of citations or self-citations the indices may increase substantially.

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Section: Resultsmentioning

confidence: 99%

“…A-index (Jin, 2006) and R-index (Jin et al, 2007) or different combinations of the rank number of papers and citations (e.g. g-index, Egghe, 2006).…”

Section: Introductionmentioning

confidence: 99%

Would it be possible to increase the Hirsch-index, π-index or CDS-index by increasing the number of publications or citations only by unity?

Vinkler

2013

Journal of Informetrics

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“…The discussion involves the introduction of an index of sparsity, inspired by the g-index from bibliometry (Egghe, 2006). Assumption 2 is satisfied if the data vector β n is sparse, if the noise is not heavy tailed, so that it can be easily separated from the data, and if the threshold or model size is near its optimal value.…”

Section: Assumptionmentioning

confidence: 99%

“…This L 2 -concentration index can be seen as the equivalent of the g-index in bibliometry (Egghe, 2006), where sparsity corresponds to a low index value. If x 1 (n) is small, then the greater part (1 − x 1 (n)) of the energy in the vector β n is concentrated the large components, accounting for only a fraction x 1 (n) of the total size of the vector.…”

Section: E the Interpretation Of Assumptionmentioning

confidence: 99%

Information criteria for variable selection under sparsity

Jansen

2014

Biometrika

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The optimization of an information criterion in a variable selection procedure leads to an additional bias, which can be substantial in sparse, high-dimensional data. The bias can be compensated by applying shrinkage while estimating within the selected models. This paper presents modified information criteria for use in variable selection and estimation without shrinkage. The analysis motivating the modified criteria follows two routes. The first, explored for signal-plus-noise observations only, goes by comparison of estimators with and without shrinkage. The second, discussed for general regression models, describes the optimization or selection bias as a double-sided effect, named a mirror effect in the paper: among the numerous insignificant variables, those with large, noisy values present themselves as being more valuable than an arbitrary variable, while in fact, they carry more noise than an arbitrary variable. The mirror effect is developed for Akaike's Information Criterion and for Mallows' C p , with special attention to the latter criterion as a stopping rule in a least angle regression routine. The result is a new stopping rule, not focusing on the quality of a lasso shrinkage selection, but on the least squares estimator without shrinkage within the same selection.

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“…Here, citations are used exclusively in order to establish quality requirements and, as a result, the score assigned to each research unit cannot be larger than the number of publications by construction (upper bounded indexes). This is the case of the h-index (Hirsch, 2005), g-index (Egghe, 2006a), h 2 -index (Kosmulski, 2006), w-index (Woeginger, 2008a), and the f-and t-indexes (Tol, 2009). On the other hand, some other (h-type) indexes have been recently proposed by which the qualitative perspective is enforced.…”

Section: Introductionmentioning

confidence: 99%

Certainty equivalent citation: generalized classes of citation indexes

Abatemarco

Dell’Anno

2012

Scientometrics

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Drawing from the existing literature on risk and inequality measurement, we implement the notion of "certainty equivalent citation" in order (i) to generalize most of the h-type citation indexes (h-, g-,g, t-, f-, w-index), and (ii) to highlight the centrality of the decision-maker's preferences on distributive aspects (concentration aversion) for the ranking of citation profiles. In order to highlight the sensitivity of citation orderings with respect to concentration aversion, an application to both simulated and real citation profiles is presented.

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Theory and practise of the g-index

Cited by 1,853 publications

References 9 publications

Would it be possible to increase the Hirsch-index, π-index or CDS-index by increasing the number of publications or citations only by unity?

Would it be possible to increase the Hirsch-index, π-index or CDS-index by increasing the number of publications or citations only by unity?

Information criteria for variable selection under sparsity

Certainty equivalent citation: generalized classes of citation indexes

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