ICAOD

Fisher Information Matrix for a 2-Parameter Cox Proportional-Hazards Model for Type One Censored Data

Fisher Information Matrix for a 2-Parameter Cox Proportional-Hazards Model for Random Censored Data

Fisher Information Matrix for a 3-Parameter Cox Proportional-Hazards Model for Type One Censored Data

Fisher Information Matrix for a 3-Parameter Cox Proportional-Hazards Model for Random Censored Data

Fisher Information Matrix for the 2-Parameter Exponential Model

Fisher Information Matrix for the Alcohol-Kinetics Model

Fisher Information Matrix for the 2-Parameter Logistic (2PL) Model

Fisher Information Matrix for the Logistic Model with Two Predictors

Fisher Information Matrix for the 4-Parameter Logistic Model

Fisher Information Matrix for the Mixed Inhibition Model

Fisher Information Matrix for the Mixed Inhibition Model.

Fisher Information Matrix for the Power Logistic Model

Fisher Information Matrix for the Sigmoid Emax Model

Returns ICA Control Optimization Parameters

ICAOD: Finding Optimal Designs for Nonlinear Models Using Imperialist Competitive Algorithm

Bayesian D-Optimal Designs

Updating an Object of Class minimax

Bayesian Compound DP-Optimal Designs

Calculates Relative Efficiency for Bayesian Optimal Designs

Returns Control Parameters for Approximating Bayesian Criteria

Returns Control Parameters for Optimizing Minimax Criteria Over The Parameter Space

Calculates Relative Efficiency for Locally Optimal Designs

Locally D-Optimal Designs

Locally DP-Optimal Designs

Calculates Relative Efficiency for Minimax Optimal Designs

Minimax and Standardized Maximin D-Optimal Designs

Locally Multiple Objective Optimal Designs for the 4-Parameter Hill Model

Assumes A Multivariate Normal Prior Distribution for The Model Parameters

Plotting minimax Objects

Printing minimax Objects

Printing sensminimax Objects

Robust D-Optimal Designs

Returns Control Parameters for Approximating The Integrals In The Bayesian Sensitivity Functions

Returns Control Parameters To Find Maximum of The Sensitivity (Derivative) Function Over The Design Space

Returns Control Parameters for Verifying General Equivalence Theorem For Minimax Optimal Designs

Verifying Optimality of Bayesian D-optimal Designs

Verifying Optimality of Bayesian Compound DP-optimal Designs

Verifying Optimality of The Locally D-optimal Designs

Verifying Optimality of The Locally DP-optimal Designs

Verifying Optimality of The Minimax and Standardized maximin D-optimal Designs

Verifying Optimality of The Multiple Objective Designs for The 4-Parameter Hill Model

Verifying Optimality of The Robust Designs

Assumes A Multivariate Skewed Normal Prior Distribution for The Model Parameters

Multivariate Student's t Prior Distribution for Model Parameters

Assume A Multivariate Uniform Prior Distribution for The Model Parameters

Updating an Object of Class minimax