Optimal Designs for Copula Models
Build probability density or mass Function
D Efficiency
Build Derivative Function for Log f
Design
Design of Experiments with Copulas
D Sensitivity
Fisher Information
Get Fisher Information
Grow Grid
Integrate Alternative
Space Validation Errors
Expand Space
Function Dimension
Grid Dimension
Integrate
Integrate Hypercube
Integrate N Function
Interval Dimension
Scatter Dimension
Space
Tangent Transform
Transform Integral
Dimension Type Attribute Values
Validate Space
Build Derivative Function for Log f
Parametric Model
Plot Design
Print Space
Reduce Design
Row Matching
Matrix Ordering Permutation
Determine Duplicate Rows
Sequence Generation
Update Parametric Model
Weighted D Efficiency
Weighted D Sensitivity
Wynn
A direct approach to optimal designs for copula models based on the Fisher information. Provides flexible functions for building joint PDFs, evaluating the Fisher information and finding optimal designs. It includes an extensible solution to summation and integration called 'nint', functions for transforming, plotting and comparing designs, as well as a set of tools for common low-level tasks.
Useful links