get_mean_control_strength: Calculate difficulty strength across multiple controls by...
In evaluator: Quantified Risk Assessment Toolkit
Description
Usage
Arguments
Value
See Also
Description
Given a set of estimation parameters, calculate control strength as the
arithmetic mean of sampled control effectiveness.
Usage
1
get_mean_control_strength(n, diff_parameters)
Arguments
n
Number of threat events to generate control effectiveness samples.
diff_parameters
Parameters to pass to sample_diff.
Value
Vector of control effectiveness.
See Also
Other OpenFAIR helpers:
compare_tef_vuln(),
openfair_tef_tc_diff_lm(),
sample_diff(),
sample_lef(),
sample_lm(),
sample_tc(),
sample_vuln(),
select_loss_opportunities()
evaluator documentation built on July 6, 2021, 9:06 a.m.
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Description Usage Arguments Value See Also
Description
Given a set of estimation parameters, calculate control strength as the arithmetic mean of sampled control effectiveness.
Usage
1 | get_mean_control_strength(n, diff_parameters)
|
Arguments
n |
Number of threat events to generate control effectiveness samples. |
diff_parameters |
Parameters to pass to |
Value
Vector of control effectiveness.
See Also
Other OpenFAIR helpers:
compare_tef_vuln(),
openfair_tef_tc_diff_lm(),
sample_diff(),
sample_lef(),
sample_lm(),
sample_tc(),
sample_vuln(),
select_loss_opportunities()
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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