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propagate (version 1.0-5)

Propagation of Uncertainty

Description

Propagation of uncertainty using higher-order Taylor expansion and Monte Carlo simulation.

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Version

Install

install.packages('propagate')

Monthly Downloads

795

Version

1.0-5

License

GPL (>= 2)

Maintainer

Andrej-Nikolai Spiess

Last Published

December 21st, 2017

Functions in propagate (1.0-5)

WelchSatter

Welch-Satterthwaite approximation to the 'effective degrees of freedom'

bigcor

Creating very large correlation/covariance matrices

makeDat

Create a dataframe from the variables defined in an expression

makeDerivs

Utility functions for creating Gradient- and Hessian-like matrices with symbolic derivatives and evaluating them in an environment

cor2cov

Converting a correlation matrix into a covariance matrix

datasets

Datasets from the GUM "Guide to the expression of uncertainties in measurement" (2008)

fitDistr

Fitting distributions to observations/Monte Carlo simulations

interval

Uncertainty propagation based on interval arithmetics

matrixStats

Fast column- and row-wise versions of variance coded in C++

mixCov

Aggregating covariances matrices and/or error vectors into a single covariance matrix

stochContr

Stochastic contribution analysis of Monte Carlo simulation-derived propagated uncertainty

summary.propagate

Summary function for 'propagate' objects

plot.propagate

Plotting function for 'propagate' objects

predictNLS

Confidence intervals for nonlinear models based on uncertainty propagation

moments

Skewness and (excess) Kurtosis of a vector of values

numDerivs

Functions for creating Gradient and Hessian matrices by numerical differentiation (Richardson's method) of the partial derivatives

print.propagate

Printing function for 'propagate' objects

propagate

Propagation of uncertainty using higher-order Taylor expansion and Monte Carlo simulation

rDistr

Creating random samples from a variety of useful distributions

statVec

Transform an input vector into one with defined mean and standard deviation