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| $NONPARAMETRIC |
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MEANING: Instructions for the NONMEM Nonparametric Step
CONTEXT: NM-TRAN Control Record
USAGE:
$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]
SAMPLE:
$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 esti-
mates 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
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 $NON-
PARAMETRIC 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 $NONPARAMETRIC, whichever one appears
first in the control stream. If the filename appears present on
both records, it must be the same on both records. If the file-
name is omitted on the second of the two records, the MSF option
must be the final option on that record. Default: No MSF is out-
put.
RECOMPUTE
Requests that the nonparametric density estimate occurring in an
input MSF should be ignored; the nonparametric estimate should be
recomputed.
EXPAND
After the parametric estimation is performed, the final eta MAP |
(or empirical Bayes estimates, EBE) estimates, based on the final |
SIGMAS, OMEGAS, and THETAS, are normally used as support points. |
When EXPAND is selected, an alternative set of EBEs are evaluated |
using the initial OMEGA values, but using the final THETAS and |
SIGMAS. |
NPSUPP=n |
Number of total support points to be used. If NPSUPP>number of |
subjects, then extra support points are randomly created from the |
final OMEGAS (even when EXPAND is selected). Only one of NPSUPP |
or NPSUPPE may be specified. |
NPSUPPE=n |
Number of total support points to be used. If NPSUPPE>number of |
subjects, then extra support points are randomly created from the |
initial, presumably inflated, OMEGAS (even when EXPAND is not |
selected). Only one of NPSUPP or NPSUPPE may be specified. |
BOOTSTRAP |
The original data set is fitted during the parametric estimation |
($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 spe- |
cific 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
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.
NPESTIM=[0|1]
The default non-parametric estimation method for assessing sup-
port point probabilities is an (non-Monte Carlo) expectation-max-
imization (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 indi-
cated 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.
UNCONDITIONAL
The Nonparametric Step is always implemented.
OMITTED
The Nonparametric Step is not implemented.
REFERENCES: None.
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