R: Summary function for 'propagate' objects

summary.propagate {propagate} | R Documentation

## Summary function for 'propagate' objects

### Description

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.

### Usage

    ## S3 method for class 'propagate'
    summary(object, ...)

### Arguments

`object` | an object returned from `propagate`.
`...` | other parameters for future methods.

### Details

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.

### Value

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

### Author(s)

Andrej-Nikolai Spiess

### References

Expression of the Uncertainty of Measurement in Calibration.
European Cooperation for Accreditation (EA-4/02), 1999.

### Examples

    EXPR1 <- expression(x^2 * sin(y))
    x <- c(5, 0.01)
    y <- c(1, 0.01)
    DF1 <- cbind(x, y)
    RES1 <- propagate(expr = EXPR1, data = DF1, type = "stat",
                      do.sim = TRUE, verbose = TRUE, nsim = 100000)
    summary(RES1)

[Package propagate version 1.0-6 Index]