LinMatrixH: Model linearization with respect to epsilon.

In PopED: Population (and Individual) Optimal Experimental Design

Description

The function performs a linearization of the model with respect to the residual variability. Derivative of model w.r.t. eps evaluated at eps=0

Usage

LinMatrixH(model_switch, xt_ind, x, a, bpop, b_ind, bocc_ind, poped.db)

Arguments

model_switch	A matrix that is the same size as xt, specifying which model each sample belongs to.
xt_ind	A vector of the individual/group sample times
x	A matrix for the discrete design variables. Each row is a group.
a	A matrix of covariates. Each row is a group.
bpop	The fixed effects parameter values. Supplied as a vector.
b_ind	vector of individual realization of the BSV terms b
bocc_ind	Vector of individual realizations of the BOV terms bocc
poped.db	A PopED database.

Value

A matrix of size (samples per individual x number of epsilons)

See Also

Other FIM: LinMatrixLH(), LinMatrixL_occ(), calc_ofv_and_fim(), ed_laplace_ofv(), ed_mftot(), efficiency(), evaluate.e.ofv.fim(), evaluate.fim(), gradf_eps(), mf3(), mf7(), mftot(), ofv_criterion(), ofv_fim()

PopED documentation built on May 21, 2021, 5:08 p.m.