Fitting a three-parameter lognormal distribution with applications to hydrogeochemical data from the National Uranium Resource Evaluation Program
The standard maximum likelihood and moment estimation procedures are shown to have some undesirable characteristics for estimating the parameters in a three-parameter lognormal distribution. A class of goodness-of-fit estimators is found which provides a useful alternative to the standard methods. The class of goodness-of-fit tests considered include the Shapiro-Wilk and Shapiro-Francia tests which reduce to a weighted linear combination of the order statistics that can be maximized in estimation problems. The weighted-order statistic estimators are compared to the standard procedures in Monte Carlo simulations. Bias and robustness of the procedures are examined and example data sets analyzed including geochemical data from the National Uranium Resource Evaluation Program.
- Research Organization:
- Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
- DOE Contract Number:
- EY-76-C-13-1664
- OSTI ID:
- 5702331
- Report Number(s):
- GJBX-175(79); K/UR-27; TRN: 80-002352
- Country of Publication:
- United States
- Language:
- English
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11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS
GEOCHEMICAL SURVEYS
DATA ANALYSIS
STATISTICS
MAXIMUM-LIKELIHOOD FIT
MOMENTS METHOD
MONTE CARLO METHOD
PROSPECTING
SIMULATION
URANIUM DEPOSITS
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GEOLOGIC DEPOSITS
MATHEMATICS
NORTH AMERICA
NUMERICAL SOLUTION
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990200* - Mathematics & Computers
050200 - Nuclear Fuels- Exploration- (-1987)