The Discrete Weibull Distribution: An Alternative for Correlated Counts with Confirmation for Microbial Counts in Water
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Abstract
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DOI: 10.1111/j.1539-6924.2010.01520.x
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References listed on IDEAS
- James D. Englehardt, 2002. "Scale Invariance of Incident Size Distributions in Response to Sizes of Their Causes," Risk Analysis, John Wiley & Sons, vol. 22(2), pages 369-381, April.
- James Englehardt & Jeff Swartout & Chad Loewenstine, 2009. "A New Theoretical Discrete Growth Distribution with Verification for Microbial Counts in Water," Risk Analysis, John Wiley & Sons, vol. 29(6), pages 841-856, June.
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Cited by:
- Riccardo Patriarca & Tianya Hu & Francesco Costantino & Giulio Di Gravio & Massimo Tronci, 2019. "A System-Approach for Recoverable Spare Parts Management Using the Discrete Weibull Distribution," Sustainability, MDPI, vol. 11(19), pages 1-15, September.
- Katherine M. Anderson & Kevin Dayaratna & Drew Gonshorowski & Steven J. Miller, 2022. "A New Benford Test for Clustered Data with Applications to American Elections," Stats, MDPI, vol. 5(3), pages 1-15, August.
- Vegard Nilsen & John Wyller, 2016. "QMRA for Drinking Water: 2. The Effect of Pathogen Clustering in Single‐Hit Dose‐Response Models," Risk Analysis, John Wiley & Sons, vol. 36(1), pages 163-181, January.
- Barbiero, A., 2019. "A bivariate count model with discrete Weibull margins," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 156(C), pages 91-109.
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