$NONPARAMETRIC

Instructions for the NONMEM Nonparametric Step.

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 $NONPARAMETRIC [MARGINALS|ETAS] [MSFO=filename] [RECOMPUTE]
                [EXPAND] [NPSUPP=n | NPSUPPE=n]
                [BOOTSTRAP [STRAT=label] [STRATF=label]]
                [PARAFILE=[filename|ON|OFF]
                [NPESTIM=[0|1]] [NPMAXITER=n]
                [UNCONDITIONAL|CONDITIONAL]  [OMITTED]

;# Example
 $NONPARAMETRIC ETAS

Discussion

Optional. Requests that the NONMEM Nonparametric Step be implemented. When present, the $ESTIMATION record must also be present and must specify METHOD=1 or POSTHOC.

For a given eta, the points of support are the vector of posthoc estimates of that eta for all individuals (i.e., the CPE values for that eta), which is essentially equal to the number of individuals in the data set.

Options

MARGINALS | ETA

MARGINALS: requests that marginal cumulatives be obtained (the default). These values are found in NONMEM global variables (See Nonparametric Density: DEN_,CDEN_)

ETAS: Requests that conditional (nonparametric) estimates of eta values be obtained. (Also called the CNPE).

MSFO=filename

A Model Specification File is output to the given filename. Filename may not contain embedded spaces. If filename contains commas, semicolons, equal signs, or parentheses, it must be enclosed in quotes (' or "). Filename may contain at most 71 characters. If filename is the same as any option of the $NONPARAMETRIC record, it must be enclosed in quotes. The MSFO option may appear without a file name. More precisely, if the $ESTIMATION record is also present, and it also specifies the MSFO option, then the filename is required only on one of the two records, $ESTIMATION or $NONPARAMETRIC, whichever one appears first in the control stream. If the filename appears present on both records, it must be the same on both records. If the filename is omitted on the second of the two records, the MSF option must be the final option on that record. Default: No MSF is output.

RECOMPUTE

Requests that the nonparametric density estimate occurring in an input MSF should be ignored; the nonparametric estimate should be recomputed.

EXPAND

After the parametric estimation is performed, the final eta MAP (or empirical Bayes estimates, EBE) estimates, based on the final SIGMAS, OMEGAS, and THETAS, are normally used as support points. When EXPAND is selected, an alternative set of EBEs are evaluated using the initial OMEGA values, but using the final THETAS and SIGMAS.

NPSUPP=n

Number of total support points to be used. If NPSUPP>number of subjects, then extra support points are randomly created from the final OMEGAS (even when EXPAND is selected). Only one of NPSUPP or NPSUPPE may be specified.

NPSUPPE=n

Number of total support points to be used. If NPSUPPE>number of subjects, then extra support points are randomly created from the initial, presumably inflated, OMEGAS (even when EXPAND is not selected). Only one of NPSUPP or NPSUPPE may be specified.

BOOTSTRAP

The original data set is fitted during the parametric estimation ($EST), and the eta support points from the original data set are used for the nonparametric version. However, a bootstrap sample, with subjects uniformly randomly selected with replacement from the original data set, is used for the nonparametric distribution analysis.

STRAT

The label of a data item that serves as the stratification. This splits the data set into distinct sub-sets, guaranteeing a specific number of subjects will be selected from each category.

STRATF

The label of a data item that contains the fraction that should represent a category in the bootstrapped data set. Without STRATF, the number of subjects to be taken from a given category is proportional to the number of subjects.

CONDITIONAL | UNCONDITIONAL

CONDITIONAL: the Nonparametric Step is implemented only when the Estimation Step terminates successfully or is not implemented (i.e., the $ESTIMATION record specifies MAXEVAL=0). This is the default.

UNCONDITIONAL: the Nonparametric Step is always implemented.

NPESTIM=[0|1]

The default non-parametric estimation method for assessing support point probabilities is an (non-Monte Carlo) expectation-maximization (EM) method. You may also choose the non-negative least squares method (NNL, [29]), with NPESTIM=1. While it is touted to be faster than EM (NNL is quadratically convergent whereas EM is linearly convergent), several tests have not indicated that NNL is any strong speed advantage. The reason is, that the computation time increases by at least the square of the number of support points (MAX(NSPSUPP,NIND)) with the NNL method, (least squares methods require matrix inversion, which is at least an N2 order process), whereas with EM the computation time increases in proporation to MAX(NSPSUPP,NIND). Thus the larger the number of support points, the greater the speed advantage of the EM method.

NPMAXITER=n

The default maximum iterations for non-parametric estimation of assessing support point probabilities is 1000, which is usually more than enough.

PARAFILE=filename

As of NONMEM 7.4, nonparametric analysis can be parallelized. PARAFILE=filename specifies a different parafile than was used for the previous step.

PARAFILE=ON turns on parallelization for the Nonparametric Step.

PARAFILE=OFF turns off parallelization for the Nonparametric Step.

OMITTED

The Nonparametric Step is not implemented.