On some methods of analysis for weather experiments

Andrey Feuerverger

doi:10.1093/biomet/66.3.655

January 1, 1979Biometrika

On some methods of analysis for weather experiments

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Key Points

To develop statistical methods using generalized densities, maximum likelihood estimation, and ancillarity for analyzing randomized weather modification trials that include predictor variables.
Formulated a two-part statistical architecture utilizing a linear logistic model to capture zero-precipitation occurrences (singularity at origin) and a gamma distribution with predictors for positive precipitation amounts.
Derived joint estimation procedures using generalized densities, maximum likelihood, and ancillarity concepts to evaluate connections between the zero-rain and positive-rain submodels.
Illustrated and evaluated the performance of the integrated models using historical data from an Australian weather modification experiment.
Established a coherent mathematical framework linking the logistic zero-rain submodel and the gamma positive-rain submodel to account for environmental covariates.
Demonstrated through the Australian experimental dataset that incorporating predictor variables into both subcomponents enables robust parameter estimation in weather modification evaluations.

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Implication

Study methodology demonstrates two-part statistical modeling in weather modification experiments, indicating improved precision when incorporating zero-precipitation records.

Abstract

Using generalized densities, maximum likelihood and ancillarity, methods are developed for the analysis of randomized weather modification experiments that incorporate predictor variables. The linear logistic form is used to model the distributional singularity at the origin, while a gamma model with predictors is developed for the component conditional on the presence of precipitation. Connexions between the component submodels are explored and illustrated using an Australian data set.

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Andrey Feuerverger (1979) studied this question.

synapsesocial.com/papers/6a19202ef3c200df1057e6b1 https://doi.org/10.1093/biomet/66.3.655

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On some methods of analysis for weather experiments

Key Points

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Cite This Study

On some methods of analysis for weather experiments

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Implication

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