R package evmix. Extreme Value Mixture Modelling, Threshold Estimation and Boundary Corrected Kernel Density Estimation. The usual distribution functions, maximum likelihood inference and model diagnostics for univariate stationary extreme value mixture models are provided. Kernel density estimation including various boundary corrected kernel density estimation methods and a wide choice of kernels, with cross-validation likelihood based bandwidth estimator. Reasonable consistency with the base functions in the ’evd’ package is provided, so that users can safely interchange most code.
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References in zbMATH (referenced in 6 articles , 1 standard article )
Showing results 1 to 6 of 6.
- Eberl, Andreas; Klar, Bernhard: Asymptotic distributions and performance of empirical skewness measures (2020)
- Jonas Moss, Martin Tveten: kdensity: An R package for kernel density estimation with parametric starts and asymmetric kernels (2019) not zbMATH
- Wijeyakulasuriya, Dhanushi A.; Hanks, Ephraim M.; Shaby, Benjamin A.; Cross, Paul C.: Extreme value-based methods for modeling elk yearly movements (2019)
- Hien D. Nguyen, Andrew T. Jones, Geoffrey J. McLachlan: logKDE: log-transformed kernel density estimation (2018) not zbMATH
- Yang Hu; Carl Scarrott: evmix: An R package for Extreme Value Mixture Modeling, Threshold Estimation and Boundary Corrected Kernel Density Estimation (2018) not zbMATH
- Scarrott, Carl: Univariate extreme value mixture modeling (2016)