R: 'ForLion' Algorithm to Find D-Optimal Designs for Experiments

# 'ForLion' Algorithm to Find D-Optimal Designs for Experiments

## Documentation for package ‘ForLion’ version 0.4.0

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package README

## Help Pages

design_initial_self | function to generate initial design with design points and the approximate allocation
discrete_rv_self | function to generate discrete uniform random variables for initial random design points in ForLion
dprime_func_self | function to calculate du/dx in the gradient of d(x, Xi), will be used in ForLion_MLM_func() function, details see Appendix C in Huang, Li, Mandal, Yang (2024)
EW_design_initial_GLM | function to generate a initial EW Design for generalized linear models
EW_design_initial_MLM | function to generate a initial EW Design for multinomial logistic models
EW_dprime_func_self | function to calculate dEu/dx in the gradient of d(x, Xi), will be used in EW_ForLion_MLM_func() function
EW_Fi_MLM_func | function to generate the expected fisher information at one design point xi for multinomial logit models
EW_ForLion_GLM_Optimal | EW ForLion for generalized linear models
EW_ForLion_MLM_Optimal | EW ForLion function for multinomial logit models
EW_liftoneDoptimal_GLM_func | EW Lift-one algorithm for D-optimal approximate design
EW_liftoneDoptimal_log_GLM_func | EW Lift-one algorithm for D-optimal approximate design in log scale
EW_liftoneDoptimal_MLM_func | function of EW liftone for multinomial logit model
EW_Xw_maineffects_self | function for calculating X=h(x) and E_w=E(nu(beta^T h(x))) given a design point x=(1,x1,...,xd)^T
Fi_MLM_func | function to generate fisher information at one design point xi for multinomial logit models
ForLion_GLM_Optimal | ForLion for generalized linear models
ForLion_MLM_Optimal | ForLion function for multinomial logit models
GLM_Exact_Design | rounding algorithm for generalized linear models
liftoneDoptimal_GLM_func | Lift-one algorithm for D-optimal approximate design
liftoneDoptimal_log_GLM_func | Lift-one algorithm for D-optimal approximate design in log scale
liftoneDoptimal_MLM_func | function of liftone for multinomial logit model
MLM_Exact_Design | rounding algorithm for multinomial logit models
nu1_cauchit_self | function to calculate first derivative of nu function given eta for cauchit link
nu1_identity_self | function to calculate first derivative of nu function given eta for identity link
nu1_logit_self | function to calculate the first derivative of nu function given eta for logit link
nu1_loglog_self | function to calculate the first derivative of nu function given eta for log-log link
nu1_log_self | function to calculate first derivative of nu function given eta for log link
nu1_probit_self | function to calculate the first derivative of nu function given eta for probit link
nu2_cauchit_self | function to calculate the second derivative of nu function given eta for cauchit link
nu2_identity_self | function to calculate the second derivative of nu function given eta for identity link
nu2_logit_self | function to calculate the second derivative of nu function given eta for logit link
nu2_loglog_self | function to calculate the second derivative of nu function given eta for loglog link
nu2_log_self | function to calculate the second derivative of nu function given eta for log link
nu2_probit_self | function to calculate the second derivative of nu function given eta for probit link
nu_cauchit_self | function to calculate w = nu(eta) given eta for cauchit link
nu_identity_self | function to calculate w = nu(eta) given eta for identity link
nu_logit_self | function to calculate w = nu(eta) given eta for logit link
nu_loglog_self | function to calculate w = nu(eta) given eta for loglog link
nu_log_self | function to calculate w = nu(eta) given eta for log link
nu_probit_self | function to calculate w = nu(eta) given eta for probit link
polynomial_sol_J3 | functions to solve 2th order polynomial function given coefficients
polynomial_sol_J4 | functions to solve 3th order polynomial function given coefficients
polynomial_sol_J5 | functions to solve 4th order polynomial function given coefficients
print.design_output | Print Method for Design Output from ForLion Algorithms
print.list_output | Print Method for list_output Objects
svd_inverse | SVD Inverse Of A Square Matrix
xmat_discrete_self | Generate initial designs within ForLion algorithms
Xw_maineffects_self | function for calculating X=h(x) and w=nu(beta^T h(x)) given a design point x = (x1,...,xd)^T