Robust Statistical Modeling of Monthly Rainfall: The Minimum Density Power Divergence Approach
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Publication:6494002
DOI10.1007/S13571-024-00324-0MaRDI QIDQ6494002
Publication date: 29 April 2024
Published in: Sankhyā. Series B (Search for Journal in Brave)
Applications of statistics to environmental and related topics (62P12) Robustness and adaptive procedures (parametric inference) (62F35)
Cites Work
- Robust fitting of mixtures using the trimmed likelihood estimator
- An adjusted boxplot for skewed distributions
- Minimum Hellinger distance estimates for parametric models
- Minimum disparity estimation for continuous models: Efficiency, distributions and robustness
- Robust estimation in the normal mixture model
- Analysis of extreme rainfall using the log logistic distribution
- On robustness of large quantile estimates of log-Gumbel and log-logistic distributions to largest elements of the observation series: Monte Carlo results vs. first order approximation.
- Calculation of the Wasserstein Distance Between Probability Distributions on the Line
- Robust and efficient estimation by minimising a density power divergence
- SOME QUICK SIGN TESTS FOR TREND IN LOCATION AND DISPERSION
- Small sample inference for gamma parameters: one‐sample and two‐sample problems
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