Xw_maineffects_self: function for calculating X=h(x) and w=nu(beta^T h(x)) given a...

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

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

Description

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

Usage

Xw_maineffects_self(x, b, link = "logit", h.func = NULL)

Arguments

x	x=(x1,...,xd) – design point/experimental setting
b	b=(b1,...,bp) – assumed parameter values
link	link = "logit" – link function, default: "logit", other links: "probit", "cloglog", "loglog", "cauchit", "log"
h.func	function h(x)=(h1(x),...,hp(x)), default (1,x1,...,xd)

Value

X=h(x)=(h1(x),...,hp(x)) – a row for design matrix

w – nu(b^t h(x))

link – link function applied

Examples

# y -> h(y)=(y1,y2,y3,y4,y5,y4*y5,1) in hfunc
hfunc.temp = function(y) {c(y,y[4]*y[5],1);};
link.temp="logit"
x.temp = c(25,1,1,1,1)
b.temp = c(-7.533386, 1.746778, -0.1937022, -0.09704664, 0.1077859, 0.2729715, 0.4293171)
Xw_maineffects_self(x.temp, b.temp, link=link.temp, h.func=hfunc.temp)

ForLion documentation built on April 11, 2025, 5:38 p.m.