Bstat: Basic statistical measures of a mathematical model results
In GSA.UN: Global Sensitivity Analysis Tool
Description
Usage
Arguments
Value
Author(s)
Examples
Description
This function calculates the mean, variance, skewness, kurtosis and
excess kurtosis of a model output, this output can be given for
different temporal periods (days, months or years).
Usage
1
Arguments
out_set
matrix of dimensions n x t, where n equals the number of
runs and t is equal to the number of temporary steps.
Value
a data frame of dimensions t x 6, here t is the number of temporary steps
and each column corresponds to a statistical measure: mean, variance,
skewness, kurtosis and excess kurtosis.
Author(s)
Camila Garcia-Echeverri <cagarciae@unal.edu.co>
Hydrodynamics of the natural media research group - HYDS
National University of Colombia - Bogota
Examples
1
2
data("out_set")
data_Bstat <- Bstat(out_set)
GSA.UN documentation built on July 10, 2020, 5:06 p.m.
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Description Usage Arguments Value Author(s) Examples
Description
This function calculates the mean, variance, skewness, kurtosis and excess kurtosis of a model output, this output can be given for different temporal periods (days, months or years).
Usage
1 |
Arguments
out_set |
matrix of dimensions n x t, where n equals the number of runs and t is equal to the number of temporary steps. |
Value
a data frame of dimensions t x 6, here t is the number of temporary steps and each column corresponds to a statistical measure: mean, variance, skewness, kurtosis and excess kurtosis.
Author(s)
Camila Garcia-Echeverri <cagarciae@unal.edu.co>
Hydrodynamics of the natural media research group - HYDS National University of Colombia - Bogota
Examples
1 2 | data("out_set")
data_Bstat <- Bstat(out_set)
|
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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