Log-normal Distributions across the Sciences: Keys and Clues

By E. Limpert, Werner A. Stahel, Markus Abbt. 2001

2,525 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Environmental Engineering

View Paper: https://www.semanticscholar.org/paper/f60a3592f480160f5cbfd5248661db7e52c411ba

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Cindy Y. Huo
2. J. Taleban
3. Leonardo Rojas-Nandayapa
4. S. T. Buckland
5. Søren Asmussen
6. Gy Zou
7. Peter Wonka
8. Jens Ledet Jensen

In Environmental Engineering

1. Ming Cui
2. John C. Femiani
3. Peter Wonka
4. Jiuxiang Hu
5. Peter Nijkamp
6. Anshuman Razdan
7. Anne E. Magurran

Citations in the corpus

• Road Network Extraction and Intersection Detection From Aerial Images by Tracking Road Footprints (2007, background): “That is, the conditional probability p(d|ω) can be modeled as a lognormal distribution [42]”
• Simple confidence intervals for lognormal means and their differences with environmental applications (2009, background): “, El-Shaarawi and Viveros, 1997; El-Shaarawi and Lin, 2007), due largely to the multiplicative central limit theorem (Limpert et al., 2001) in the sense that multiplication of a large number of random variables will result in a composite variable which can be approximated by the lognormal distributi”
• Why are Normal Distributions Normal? (2014, background): “distributed turning out to be log-normally distributed (Limpert et al., 2001), or distributed in some other way (e.”
• Equivalence of Granger Causalityand Transfer Entropy: A Generalization. (2011, background): “However, some measurements can however on small data sample fit both normal and log-normal distributions (for example body height [19]).”
• Self-organized aggregation in cockroaches (2005, methodology): “The distribution of angles for individuals that left the peripheral zone for the centre of the arena was fitted by a log-normal distribution (Limpert et al. 2001), specified by two parameters that could easily be incorporated into a numerical model (geometric mean / SDZ 36.”
• COMPREHENSIVE ANALYSIS OF CORONAL MASS EJECTION MASS AND ENERGY PROPERTIES OVER A FULL SOLAR CYCLE (2010, background): “…P of the logarithm of a random variable x is normally distributed with a mean µ, and standard deviation of σ (see also Yurchyshyn et al. (2005); Limpert et al. (2001)) P = exp−( log x− µ√ 2σ )2 (5) then the variable is log-normally distributed with probability density function f(x) as f(x)…”
• The bubble size distribution in wheat flour dough (2006, background): “As with many variables in real life (Crow, 1988; Johannesson & Mitson, 1983; Limpert, Stahel, & Abbt, 2001; Shimizu & Crow, 1988), gas bubble break-up in dough can be viewed as a log-normal phenomenon (Campbell, 1991; Shimiya & Nakamura, 1997).”