Description Usage Arguments Details Value Author(s) References Examples

View source: R/summary.propagate.R

Provides a printed summary of the results obtained by `propagate`

, such as statistics of the first/second-order uncertainty propagation, Monte Carlo simulation, the covariance matrix, symbolic as well as evaluated versions of the Gradient ("sensitivity") and Hessian matrices, relative contributions, the coverage factor and the Welch-Satterthwaite degrees of freedom. If `do.sim = TRUE`

was set in `propagate`

, skewness/kurtosis and Shapiro-Wilks/Kolmogorov-Smirnov tests for normality are calculated on the Monte-Carlo evaluations.

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`object` |
an object returned from |

`...` |
other parameters for future methods. |

Calculates the "sensitivity"" *S_i* of each variable *x_i* to the propagated uncertainty, as defined in the *Expression of the Uncertainty of Measurement in Calibration, Eqn 4.2, page 9* (see 'References'):

*S_i = \mathrm{eval}≤ft(\frac{\partial f}{\partial x_i}\right)*

The "contribution" matrix is then *\mathbf{C} = \mathbf{SS}^T\mathbf{Σ}*, where *\mathbf{Σ}* is the covariance matrix. In the implementation here, the "relative contribution" matrix *\mathbf{C}_{\mathrm{rel}}* is rescaled to sum up to 1.

A printed output with the items listed in 'Description'.

Andrej-Nikolai Spiess

Expression of the Uncertainty of Measurement in Calibration.

European Cooperation for Accreditation (EA-4/02), 1999.

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

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