# stochContr: Stochastic contribution analysis of Monte Carlo... In propagate: Propagation of Uncertainty

## Description

Conducts a "stochastic contribution analysis" by calculating the change in propagated uncertainty when each of the simulated variables is kept constant at its mean, i.e. the uncertainty is removed.

## Usage

 1 stochContr(prop, plot = TRUE) 

## Arguments

 prop a propagate object. plot logical. If TRUE, a boxplot with the original and mean-value propagated distribution.

## Details

This function takes the Monte Carlo simulated data X_n from a propagate object (...\$datSIM), sequentially substitutes each variable β_i by its mean \bar{β_i} and then re-evaluates the output distribution Y_n = f(β, X_n). Optional boxplots are displayed that compare the original Y_n\mathrm{(orig)} to those obtained from removing σ from each β_i. Finally, the relative contribution C_i for all β_i is calculated by C_i = σ(Y_n\mathrm{(orig)})-σ(Y_n), and divided by its sum so that ∑_{i=1}^n C_i = 1.

## Value

The relative contribution C_i for all variables.

## Author(s)

Andrej-Nikolai Spiess

## Examples

 1 2 3 4 5 6 7 a <- c(15, 1) b <- c(100, 5) c <- c(0.5, 0.02) DAT <- cbind(a, b, c) EXPR <- expression(a * b^sin(c)) RES <- propagate(EXPR, DAT, nsim = 100000) stochContr(RES) 

propagate documentation built on May 7, 2018, 1:03 a.m.