Technological improvements or climate change? Bayesian modeling of time-varying conformance to Benford’s Law

• Published in: PloS one Vol. 14; no. 4; p. e0213300
• Main Authors: Lee, Junho, de Carvalho, Miguel
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 12.04.2019; Public Library of Science (PLoS)
• Subjects: Archives & records; Bayes Theorem; Bayesian analysis; Bias; Climate Change; Climate models; Computer and Information Sciences; Cyclone tracks; Cyclones; Databases, Factual; Datasets; Digits; Earth Sciences; Environmental research; Fraud; Generalized linear models; Geosphere; Global temperature changes; Heterogeneity; Homogeneity; Humans; Methods; Multilevel analysis; Numerical analysis; Physical Sciences; Probability distributions; Quality assessment; Quality Control; Random variables; Research and Analysis Methods; Storms; Tornadoes; Tropical cyclone tracks; Tropical cyclones; United Kingdom > UK
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0213300

We develop a Bayesian time-varying model that tracks periods at which conformance to Benford's Law is lower. Our methods are motivated by recent attempts to assess how the quality and homogeneity of large datasets may change over time by using the First-Digit Rule. We resort to a smooth multinomial logistic model which captures the dynamics governing the proportion of first digits, and apply the proposed model to global tropical cyclone tracks over the past two centuries. Our findings indicate that cumulative technological improvements may have only had a moderate influence on the homogeneity of the dataset, and hint that recent heterogeneity could be due to other drivers.