Propagation of Uncertainty
Creating very large correlation/covariance matrices
Converting a correlation matrix into a covariance matrix
Datasets from the GUM "Guide to the expression of uncertainties in mea...
Fitting distributions to observations/Monte Carlo simulations
Uncertainty propagation based on interval arithmetics
Create a dataframe from the variables defined in an expression
Utility functions for creating Gradient- and Hessian-like matrices wit...
Fast column- and row-wise versions of variance coded in C++
Aggregating covariances matrices and/or error vectors into a single co...
Skewness and (excess) Kurtosis of a vector of values
Functions for creating Gradient and Hessian matrices by numerical diff...
Plotting function for 'propagate' objects
Confidence/prediction intervals for (weighted) nonlinear models based ...
Propagation of uncertainty using higher-order Taylor expansion and Mon...
Creating random samples from a variety of useful distributions
Transform an input vector into one with defined mean and standard devi...
Stochastic contribution analysis of Monte Carlo simulation-derived pro...
Summary function for 'propagate' objects
Welch-Satterthwaite approximation to the 'effective degrees of freedom...
Propagation of uncertainty using higher-order Taylor expansion and Monte Carlo simulation. Calculations of propagated uncertainties are based on matrix calculus including covariance structure according to Arras 1998 <doi:10.3929/ethz-a-010113668> (first order), Wang & Iyer 2005 <doi:10.1088/0026-1394/42/5/011> (second order) and BIPM Supplement 1 (Monte Carlo) <doi:10.59161/JCGM101-2008>.