The covXtreme software provides functionality for estimation of marginal and conditional extreme value models, non-stationary with respect to covariates, and environmental design contours. Generalised Pareto (GP) marginal models of peaks over threshold are estimated, using a piecewise-constant representation for the variation of GP threshold and scale parameters on the (potentially multidimensional) covariate domain of interest. The conditional variation of one or more associated variates, given a large value of a single conditioning variate, is described using the conditional extremes model of Heffernan and Tawn (2004), the slope term of which is also assumed to vary in a piecewise constant manner with covariates. Optimal smoothness of marginal and conditional extreme value model parameters with respect to covariates is estimated using cross-validated roughness-penalised maximum likelihood estimation. Uncertainties in model parameter estimates due to marginal and conditional extreme value threshold choice, and sample size, are quantified using a bootstrap resampling scheme. Estimates of environmental contours using various schemes, including the direct sampling approach of Huseby et al. 2013, are calculated by simulation or numerical integration under fitted models. The software was developed in MATLAB for metocean applications, but is applicable generally to multivariate samples of peaks over threshold. The software can be downloaded from GitHub, with an accompanying user guide.

翻译：covXtreme软件提供了对协变量非平稳的边际和条件极值模型进行估计以及环境设计轮廓的功能。采用广义帕累托（GP）边际模型估计超阈值峰值，利用分段常数表示法描述GP阈值和尺度参数在（潜在多维）协变量域上的变化。对于给定单个条件变量大值的一或多个相关变量的条件变化，采用Heffernan与Tawn（2004）的条件极值模型进行描述，该模型的斜率项也假设以分段常数方式随协变量变化。通过交叉验证的粗糙度惩罚极大似然估计，估算边际和条件极值模型参数相对于协变量的最优平滑度。模型参数估计中因边际和条件极值阈值选择及样本量引起的不确定性，通过自助重采样方案进行量化。采用包括Huseby等人（2013）直接抽样方法在内的多种方案，通过拟合模型下的模拟或数值积分计算环境轮廓估计值。该软件基于MATLAB开发，专为海洋气象应用设计，但可通用处理超阈值峰值多变量样本。软件可从GitHub下载，并附有用户指南。