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ForLion

ForLion R package

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Install

install.packages('ForLion')

Monthly Downloads

275

Version

0.3.0

License

MIT + file LICENSE

Maintainer

Siting Lin

Last Published

June 27th, 2025

Functions in ForLion (0.3.0)

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
Xw_maineffects_self

function for calculating X=h(x) and w=nu(beta^T h(x)) given a design point x = (x1,...,xd)^T
ForLion-package

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

function to generate initial design with design points and the approximate allocation
liftoneDoptimal_GLM_func

Lift-one algorithm for D-optimal approximate design
nu_logit_self

function to calculate w = nu(eta) given eta for logit link
nu1_logit_self

function to calculate the first derivative of nu function given eta for logit link
nu1_probit_self

function to calculate the first derivative of nu function given eta for probit link
nu1_loglog_self

function to calculate the first derivative of nu function given eta for log-log link
nu_loglog_self

function to calculate w = nu(eta) given eta for loglog link
print.list_output

Print Method for list_output Objects
nu2_cauchit_self

function to calculate the second derivative of nu function given eta for cauchit link
print.design_output

Print Method for Design Output from ForLion Algorithms
nu1_identity_self

function to calculate first derivative of nu function given eta for identity link
MLM_Exact_Design

rounding algorithm for multinomial logit models
nu1_log_self

function to calculate first derivative of nu function given eta for log link
nu_identity_self

function to calculate w = nu(eta) given eta for identity link
nu_log_self

function to calculate w = nu(eta) given eta for log 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
polynomial_sol_J5

functions to solve 4th order polynomial function given coefficients
liftoneDoptimal_log_GLM_func

Lift-one algorithm for D-optimal approximate design in log scale
nu1_cauchit_self

function to calculate first derivative of nu function given eta for cauchit link
polynomial_sol_J4

functions to solve 3th order polynomial function given coefficients
nu2_probit_self

function to calculate the second derivative of nu function given eta for probit link
svd_inverse

SVD Inverse Of A Square Matrix
nu_cauchit_self

function to calculate w = nu(eta) given eta for cauchit link
liftoneDoptimal_MLM_func

function of liftone for multinomial logit model
xmat_discrete_self

Generate initial designs within ForLion algorithms
nu_probit_self

function to calculate w = nu(eta) given eta for probit link
nu2_log_self

function to calculate the second derivative of nu function given eta for log link
nu2_identity_self

function to calculate the second derivative of nu function given eta for identity link
polynomial_sol_J3

functions to solve 2th order polynomial function given coefficients
EW_ForLion_GLM_Optimal

EW ForLion for generalized linear models
EW_Fi_MLM_func

function to generate the expected fisher information at one design point xi for multinomial logit models
EW_ForLion_MLM_Optimal

EW ForLion function for multinomial logit models
EW_design_initial_GLM

function to generate a initial EW Design for generalized linear models
EW_liftoneDoptimal_log_GLM_func

EW Lift-one algorithm for D-optimal approximate design in log scale
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
EW_liftoneDoptimal_GLM_func

EW Lift-one algorithm for D-optimal approximate design
EW_liftoneDoptimal_MLM_func

function of EW liftone for multinomial logit model
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
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)
GLM_Exact_Design

rounding algorithm for generalized linear models
ForLion_MLM_Optimal

ForLion function for multinomial logit models