approxtoexact_constrained_func |
Convert the approximate allocation (proportion) to exact allocation (integer) with bounded constraint (ni <= Ni) |
approxtoexact_func |
Convert the approximate allocation (proportion) to exact allocation (integer) without constraint |
constrained_uniform |
Find (constrained) uniform exact allocation of the study for bounded design |
Fdet_func_GLM |
Determinant of Fisher information matrix for GLM |
Fdet_func_MLM |
Determinant of Fisher information matrix of multinomial logistic model (MLM) |
Fdet_func_unif |
Determinant function to be used for finding constrained uniform samplings |
Fi_func_MLM |
Generate Fisher information matrix F_x at a design point x_i for Multinomial logistic regression model |
F_func_GLM |
Fisher information matrix of generalized linear model (GLM) |
F_func_MLM |
The Fisher information matrix of multinomial logistic model (MLM) |
iset_func_trauma |
trauma_data example (see Huang, Tong, Yang (2023)) specific function for finding index set that if allocation of that index add "1", the new allocation still falls within the constraint Used in approxtoexact_constrained_func() |
iset_func_trial |
trial_data example (see Huang, Tong, Yang (2023)) specific function for finding index set that if allocation of that index add "1", the new allocation still falls within the constraint Used in approxtoexact_constrained_func() |
liftone_constrained_GLM |
Find constrained D-optimal approximate design for generalized linear models (GLM) |
liftone_constrained_MLM |
Find constrained D-optimal designs for Multinomial Logit Models (MLM) |
liftone_GLM |
Unconstrained lift-one algorithm to find D-optimal allocations for GLM |
liftone_MLM |
Unconstrained lift-one algorithm to find D-optimal allocations for MLM |
trauma_data |
Trauma data with multinomial response |
trial_data |
Generated clinical trial data with binary response |
W_func_GLM |
Calculate the diagonal elements nu of Fisher information matrix |