Package: ForLion 0.4.0

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

Designing experimental plans that involve both discrete and continuous factors with general parametric statistical models using the 'ForLion' algorithm and 'EW ForLion' algorithm. The algorithms searches for locally optimal designs and EW optimal designs under the D-criterion. See Huang, Y., Li, K., Mandal, A., & Yang, J., (2024) <doi:10.1007/s11222-024-10465-x> and Lin, S., Huang, Y., & Yang, J. (2025) <doi:10.48550/arXiv.2505.00629>.

Authors:Yifei Huang [aut], Siting Lin [aut, cre], Jie Yang [aut]

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manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
ForLion/json (API)

# Install 'ForLion' in R:

install.packages('ForLion', repos = c('https://lin-siting.r-universe.dev', 'https://cloud.r-project.org'))

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

2.70 score 1 scripts 244 downloads 45 exports 7 dependencies

Last updated from:07ac8a1dc3. Checks:9 OK. Indexed: yes.

Target	Result	Time
linux-devel	OK	140
source / vignettes	OK	465
linux-release	OK	133
macos-release	OK	204
macos-oldrel	OK	210
windows-devel	OK	97
windows-release	OK	104
windows-oldrel	OK	67
wasm-release	OK	93

Exports:design_initial_self discrete_rv_self dprime_func_self EW_design_initial_GLM EW_design_initial_MLM EW_dprime_func_self EW_Fi_MLM_func EW_ForLion_GLM_Optimal EW_ForLion_MLM_Optimal EW_liftoneDoptimal_GLM_func EW_liftoneDoptimal_log_GLM_func EW_liftoneDoptimal_MLM_func EW_Xw_maineffects_self Fi_MLM_func ForLion_GLM_Optimal ForLion_MLM_Optimal GLM_Exact_Design liftoneDoptimal_GLM_func liftoneDoptimal_log_GLM_func liftoneDoptimal_MLM_func MLM_Exact_Design nu_cauchit_self nu_identity_self nu_log_self nu_logit_self nu_loglog_self nu_probit_self nu1_cauchit_self nu1_identity_self nu1_log_self nu1_logit_self nu1_loglog_self nu1_probit_self nu2_cauchit_self nu2_identity_self nu2_log_self nu2_logit_self nu2_loglog_self nu2_probit_self polynomial_sol_J3 polynomial_sol_J4 polynomial_sol_J5 svd_inverse xmat_discrete_self Xw_maineffects_self

Dependencies:cubature GPArotation lattice mnormt nlme psych Rcpp

Introduction to ForLion package

Rendered fromIntro_to_ForLion.Rmdusingknitr::rmarkdown

Last update: 2026-02-15
Started: 2025-02-11

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

Package: ForLion 0.4.0

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

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