View source: R/EW_design_initial_GLM.R
EW_design_initial_GLM | R Documentation |
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",
delta0 = 1e-06,
epsilon = 1e-12,
maxit = 1000
)
k.continuous |
number of continuous variables |
factor.level |
list of distinct factor levels, “(min, max)” for continuous factors that always come first, finite sets for discrete factors. |
Integral_based |
TRUE or FALSE, whether or not integral-based EW D-optimality is used, FALSE indicates sample-based EW D-optimality is used. |
b_matrix |
matrix of bootstrapped or simulated parameter values. |
joint_Func_b |
prior distribution function of model parameters |
Lowerbounds |
vector of lower ends of ranges of prior distribution for model parameters. |
Upperbounds |
vector of upper ends of ranges of prior distribution for model parameters. |
xlist_fix |
list of discrete factor experimental settings under consideration, default NULL indicating a list of all possible discrete factor experimental settings will be used. |
lvec |
lower limit of continuous variables |
uvec |
upper limit of continuous variables |
h.func |
function, is used to transfer the design point to model matrix (e.g. add interaction term, add intercept) |
link |
link function, default "continuation", other options "baseline", "adjacent" and "cumulative" |
delta0 |
tuning parameter, the distance threshold, || x_i(0) - x_j(0) || >= delta0 |
epsilon |
determining f.det > 0 numerically, f.det <= epsilon will be considered as f.det <= 0 |
maxit |
maximum number of iterations |
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
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.