Extreme Value Analysis (EVA) in Python
-
Updated
Feb 22, 2024 - Python
Extreme Value Analysis (EVA) in Python
Functions from the book "Reinsurance: Actuarial and Statistical Aspects"
R package for Bayesian spatial and spatiotemporal GLMMs with possible extremes
Ratio-of-Uniforms Sampling for Bayesian Extreme Value Analysis
Threshold Selection and Uncertainty for Extreme Value Analysis
Some movies to teach statistical concepts
Calculate the minimum absolute value of a double-precision floating-point strided array, ignoring NaN values.
Statistical methods for the analysis of excess lifetimes
Collection of Code for ML algorithms and other stuff in the RP Rainfall Extremes in CLEX
R package. Main goals are to fit models to the clone size distribution of the TCR repertoire, and to perform model-based comparative analysis of samples.
Niche-based vulnerability of species and communities.
Generalized fiducial inference for extremes.
Predicting weather extremes (frequency, intensity and spatial dependence) with machine learning
Estimation of the Extremal Index
Calculate the minimum value of a double-precision floating-point strided array according to a mask.
Supplementary materials to my internship's report.
Add a description, image, and links to the extremes topic page so that developers can more easily learn about it.
To associate your repository with the extremes topic, visit your repo's landing page and select "manage topics."