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ForLion

ForLion R package

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Install

install.packages('ForLion')

Monthly Downloads

232

Version

0.1.0

License

MIT + file LICENSE

Maintainer

Siting Lin

Last Published

February 11th, 2025

Functions in ForLion (0.1.0)

EW_liftoneDoptimal_GLM_func

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

function to generate random initial design with design points and the approximate allocation
MLM_Exact_Design

Approximation to exact design algorithm for multinomial logit model
liftoneDoptimal_GLM_func

Lift-one algorithm for D-optimal approximate design
ForLion_MLM_Optimal

ForLion function for multinomial logit models
nu1_loglog_self

function to calculate the first derivative of nu function given eta for log-log link
nu2_cauchit_self

function to calculate the second derivative of nu function given eta for cauchit link
nu1_log_self

function to calculate first derivative of nu function given eta for log link
nu2_loglog_self

function to calculate the second derivative of nu function given eta for loglog link
nu2_probit_self

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

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

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

function to calculate w = nu(eta) given eta for probit link
nu2_identity_self

function to calculate the second derivative of nu function given eta for identity link
nu1_identity_self

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

function for calculating X=h(x) and w=nu(beta^T h(x)) given a design point x = (x1,...,xd)^T
nu2_log_self

function to calculate the second derivative of nu function given eta for log link
nu1_cauchit_self

Function to calculate first derivative of nu function given eta for cauchit link
nu2_logit_self

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

SVD Inverse Of A Square Matrix This function returns the inverse of a matrix using singular value decomposition. If the matrix is a square matrix, this should be equivalent to using the solve function. If the matrix is not a square matrix, then the result is the Moore-Penrose pseudo inverse.
nu_logit_self

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

Function to calculate w = nu(eta) given eta for log link
nu1_probit_self

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

function of liftone for multinomial logit model
nu_identity_self

Function to calculate w = nu(eta) given eta for identity link
nu_cauchit_self

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

Lift-one algorithm for D-optimal approximate design in log scale
print.design_output

Print Method for Design Output from ForLion Algorithm
print.list_output

Print Method for list_output Objects
xmat_discrete_self

Generate GLM random initial designs within ForLion algorithm
EW_ForLion_MLM_Optimal

EW ForLion function for multinomial logit models
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_design_initial_self

function to generate random initial design with design points and the approximate allocation (For EW)
Fi_MLM_func

Function to generate fisher information at one design point xi for multinomial logit 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_Xw_maineffects_self

function for calculating X=h(x) and E_w=E(nu(beta^T h(x))) give a design point x=(1,x1,...,xd)^T
EW_Fi_MLM_func

Function to generate the Expectation of fisher information at one design point xi for multinomial logit models
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_ForLion_GLM_Optimal

EW ForLion for generalized linear models
ForLion-package

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

ForLion for generalized linear models
GLM_Exact_Design

Approximation to exact design algorithm for generalized linear model
discrete_rv_self

function to generate discrete uniform random variables for initial random design points in ForLion