function to generate a initial EW Design for generalized linear models
EW_design_initial_GLM(
k.continuous,
factor.level,
Integral_based,
b_matrix,
joint_Func_b,
Lowerbounds,
Upperbounds,
xlist_fix = NULL,
lvec,
uvec,
h.func,
link = "continuation",
delta = 1e-06,
epsilon = 1e-12,
maxit = 1000
)X matrix of initial design point
p0 initial random approximate allocation
f.det the determinant of the expected Fisher information matrix for the initial design
number of continuous variables
lower, upper limit of continuous variables, and discrete levels of categorical variables, continuous factors come first
TRUE or FALSE, if TRUE then we will find the integral-based EW D-optimality otherwise we will find the sample-based EW D-optimality
The matrix of the sampled parameter values of beta
The prior joint probability distribution of the parameters
The lower limit of the prior distribution for each parameter
The upper limit of the prior distribution for each parameter
the restricted discrete settings to be chosen, default to NULL, if NULL, will generate a discrete uniform random variables
lower limit of continuous variables
upper limit of continuous variables
function, is used to transfer the design point to model matrix (e.g. add interaction term, add intercept)
link function, default "continuation", other options "baseline", "adjacent" and "cumulative"
tuning parameter, the distance threshold, || x_i(0) - x_j(0) || >= delta
determining f.det > 0 numerically, f.det <= epsilon will be considered as f.det <= 0
maximum number of iterations