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Two journal-level indicators, respectively the mean ($m^i$) and the standarddeviation ($v^i$) are proposed to be the core indicators of each journal and weshow that quite several other indicators can be calculated from those two coreindicators, assuming that yearly citation counts of papers in each journalfollows more or less a log-normal distribution. Those other journal-levelindicators include journal h index, journal one-by-one-sample comparisoncitation success index $S_j^i$, journal multiple-sample $K^i-K^j$ comparisonsuccess rate $S_{j,K^j}^{i,K^i }$, and minimum representative sizes$\kappa_j^i$ and $\kappa_i^j$, the average ranking of all papers in a journalin a set of journals($R^t$). We find that those indicators are consistent withthose calculated directly using the raw citation data($C^i=\{c_1^i,c_2^i,\dots,c_{N^i}^i \},\forall i$) of journals. In addition toits theoretical significance, the ability to estimate other indicators fromcore indicators has practical implications. This feature enables individualswho lack access to raw citation count data to utilize other indicators bysimply using core indicators, which are typically easily accessible.

data science and informetrics

Two indicators rule them all: Mean and standard deviation used to  calculate other journal indicators based on log-normal distribution of  citation counts