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Berger, A and Twelves, I (2018)

On the significands of uniform random variables

Journal of Applied Probability 55(2), pp. 353-367.

ISSN/ISBN: Not available at this time. DOI: 10.1017/jpr.2018.23



Abstract: For all α > 0 and real random variables X, we establish sharp bounds for the smallest and the largest deviation of αX from the logarithmic distribution also known as Benfordís law. In the case of uniform X, the value of the smallest possible deviation is determined explicitly. Our elementary calculation puts into perspective the recurring claims that a random variable conforms to Benfordís law, at least approximately, whenever it has large spread.


Bibtex:
@article {, AUTHOR = {Arno Berger and Isaac Twelves}, TITLE = {On the significands of uniform random variables}, JOURNAL = {Journal of Applied Probability}, YEAR = {2018}, VOLUME = {55}, NUMBER = {2}, PAGES = {353-367}, DOI = {10.1017/jpr.2018.23}, }


Reference Type: Journal Article

Subject Area(s): Analysis, Probability Theory