The Bias in Moment Estimators for Parameters of Drop Size Distribution Functions: Sampling from Exponential Distributions

By Paul L. Smith, Donna Kliche. 2005

61 citations recorded by the source corpus.

Subfields: Atmospheric Science, Environmental Engineering, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/1c91a5136509bf27eaafcd48774ab2ed6f86985e

How researchers see this paper

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

In Atmospheric Science

1. Roger W. Johnson
2. Donna Kliche
3. Paul L. Smith

In Environmental Engineering

1. Roger W. Johnson
2. Donna Kliche
3. Paul L. Smith

In Global and Planetary Change

1. Roger W. Johnson
2. Donna Kliche
3. Paul L. Smith

Citations in the corpus

• Estimation of Gamma Raindrop Size Distribution Parameters: Statistical Fluctuations and Estimation Errors (2009, background): “As underlined by Smith and Kliche (2005), moment method (MM) estimators are biased, whereas ML estimators are asymptotically unbiased, but have significant problems when missing observations of small drops are taken into account.”
• L-Moment Estimators as Applied to Gamma Drop Size Distributions (2008, methodology): “However, the moment method is known to be biased (Robertson and Fryer, 1970; Wallis, 1974; Haddad et al., 1996, 1997; Smith and Kliche, 2005; Uijlenhoet et al., 2006), which means that the fitted functions often do not correctly represent the raindrop populations, and sometimes not even the sample”