sensitivity: Run a one-dimensional sensitivity analysis
In DTWilson/BOSSS: Bayesian Optimisation for Simulation-based Sample Size
sensitivity R Documentation
Run a one-dimensional sensitivity analysis
Description
Run a one-dimensional sensitivity analysis
Usage
sensitivity(sa_hypothesis, design, problem, solution, num_eval = 20, N = 100)
Arguments
sa_hypothesis
Data frame defining the SA variable and its bounds
design
Design to be tested
problem
BOSSS problem
solution
BOSSS solution
num_eval
Number of points to evaluate
N
Number of MC samples to use in each evaluation
Value
A matrix of estimated means and their variances for each simulation
output over the SA variable range.
DTWilson/BOSSS documentation built on April 14, 2025, 8:35 a.m.
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.
| sensitivity | R Documentation |
Run a one-dimensional sensitivity analysis
Description
Run a one-dimensional sensitivity analysis
Usage
sensitivity(sa_hypothesis, design, problem, solution, num_eval = 20, N = 100)
Arguments
sa_hypothesis |
Data frame defining the SA variable and its bounds |
design |
Design to be tested |
problem |
BOSSS problem |
solution |
BOSSS solution |
num_eval |
Number of points to evaluate |
N |
Number of MC samples to use in each evaluation |
Value
A matrix of estimated means and their variances for each simulation output over the SA variable range.
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.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.