## File Name: noharm_sirt_optim_function.R
## File Version: 0.18
noharm_sirt_optim_function <- function(x, parm_table, parm_index, I, D,
b0.jk, b1.jk, b2.jk, b3.jk, pm, wgtm, use_rcpp=FALSE )
{
parm_table <- noharm_sirt_partable_include_par(par=x, parm_table=parm_table)
Fmat <- noharm_sirt_create_parameter_matrices("F", parm_table=parm_table, parm_index=parm_index)
Pmat <- noharm_sirt_create_parameter_matrices("P", parm_table=parm_table, parm_index=parm_index)
Psimat <- noharm_sirt_create_parameter_matrices("Psi", parm_table=parm_table, parm_index=parm_index)
#- implied covariance: gamma values
gamma_val <- noharm_sirt_implied_cov(Fmat=Fmat, Pmat=Pmat, Psimat=Psimat)
## gamma_ii
gamma_diag <- diag(gamma_val)
delta <- 1 + gamma_diag
#- compute least squares function
if (!use_rcpp){
val <- noharm_sirt_optim_function_R( gamma_val=gamma_val, delta=delta, I=I,
wgtm=wgtm, pm=pm, b0.jk=b0.jk, b1.jk=b1.jk, b2.jk=b2.jk, b3.jk=b3.jk )
} else {
val <- sirt_rcpp_noharm_sirt_optim_fn_rcpp( gamma_val=gamma_val,
delta=delta, I=I, wgtm=wgtm, pm=pm, b0_jk=b0.jk, b1_jk=b1.jk, b2_jk=b2.jk,
b3_jk=b3.jk )
}
#-- output
return(val)
}
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