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ismev - An Introduction to Statistical Modeling of Extreme Values

Functions to support the computations carried out in `An Introduction to Statistical Modeling of Extreme Values' by Stuart Coles. The functions may be divided into the following groups; maxima/minima, order statistics, peaks over thresholds and point processes.

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6.56 score 1 stars 21 dependents 533 scripts 13k downloads

verification - Weather Forecast Verification

Utilities for verifying discrete, continuous and probabilistic forecasts, and forecasts expressed as parametric distributions are included.

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5.91 score 3 stars 10 dependents 617 scripts 1.5k downloads

extRemes - Extreme Value Analysis

General functions for performing extreme value analysis. In particular, allows for inclusion of covariates into the parameters of the extreme-value distributions, as well as estimation through MLE, L-moments, generalized (penalized) MLE (GMLE), as well as Bayes. Inference methods include parametric normal approximation, profile-likelihood, Bayes, and bootstrapping. Some bivariate functionality and dependence checking (e.g., auto-tail dependence function plot, extremal index estimation) is also included. For a tutorial, see Gilleland and Katz (2016) <doi: 10.18637/jss.v072.i08> and for bootstrapping, please see Gilleland (2020) <doi: 10.1175/JTECH-D-20-0070.1>.

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5.62 score 2 stars 7 dependents 696 scripts 2.8k downloads

distillery - Method Functions for Confidence Intervals and to Distill Information from an Object

Some very simple method functions for confidence interval calculation, bootstrap resampling aimed at atmospheric science applications, and to distill pertinent information from a potentially complex object; primarily used in common with packages extRemes and SpatialVx. To reference this package and for a tutorial on the bootstrap functions, please see Gilleland (2020) <doi: 10.1175/JTECH-D-20-0069.1> and Gilleland (2020) <doi: 10.1175/JTECH-D-20-0070.1>.

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3.14 score 9 dependents 25 scripts 2.1k downloads

smoothie - Two-Dimensional Field Smoothing

Perform two-dimensional smoothing for spatial fields using FFT and the convolution theorem (see Gilleland 2013, <doi:10.5065/D61834G2>).

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2.19 score 2 dependents 26 scripts 323 downloads

SpatialVx - Spatial Forecast Verification

Spatial forecast verification refers to verifying weather forecasts when the verification set (forecast and observations) is on a spatial field, usually a high-resolution gridded spatial field. Most of the functions here require the forecast and observed fields to be gridded and on the same grid. For a thorough review of most of the methods in this package, please see Gilleland et al. (2009) <doi: 10.1175/2009WAF2222269.1> and for a tutorial on some of the main functions available here, see Gilleland (2022) <doi: 10.5065/4px3-5a05>.

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2.17 score 2 stars 74 scripts 425 downloads