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Model linearization with respect to epsilon.

Source: R/LinMatrixH.R
LinMatrixH.Rd

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()