Fix bug where models where omega boundary warnings caused problems in estimation (#490)
Created a new api for pre-processing ui, allowing adding arbitrary hooks. As written now, this includes literal fix and zero omega as well as added the new rxode2 ui processing.
Fixed compilation to only use -I in most systems for maximum compatibility
Now when optimizing only a single parameter with focei-family,
will change to use stats::optimize() for the outer problem (#481)
When estimating with all fixed population parameters, do a posthoc estimation.
Internally removed assignInMyNamespace() replacing with
nlmixr2global, which fixes some edge case bugs where the nlmixr2
environment was not reset properly.
Treated edge case where all initial parameters are zero and change scaling from scaled to unscaled (#486)
Added mu4 referencing that will change string expressions to
rxode2 numeric values. This allows derived strings to also be
treated as mu expressions (#484)
focei covariance step when many omega values are fixed #482No binary linking to rxode2, lbfgsb3c and n1q1, which means
that updating these will not make nlmixr2est crash without
recompiling.
New mu3 referencing will take context from the model to see if the
algebraic expression can be completed from defined model variables;
These variable would have to be unique.
Saem non-mu reference input parameters/covariates were fixed so they work correctly with fixed parameters (Issue #445)
Focei changed back to having a lower bound for standard deviations
when not specified. This means that best model fits may change. You
can revert to the old settings by using
foceiControl(sdLowerFact=0.0). You can also change the factors to
other values than the default value, that is
foceiControl(sdLowerFact=0.000001) for instance which would
multiply the initial value by 0.000001 when either the lower bound
isn't specified or the lower bound is specified as zero for the
error estimates related to error-based standard deviations.
In nlmixr2, expressions are optimized. Because of that
optimization, numerical rounding differences can cause different
directions in optimization when fixing parameters in the model
vs. fixing the parameters manually.
This means that the fixed parameters in a model vs hard-coded fixed parameters could give different values in the final model.
A new option literalFix was introduced which change the fixed
population parameters to constants in the model while running the
optimization. This makes the output of fixing within the model and
fixing manually the same (which is what is likely expected). The
default is for this to be turned on (ie. literalFix=TRUE). You
can get back the old behavior by using the option
literalFix=FALSE.
In saem, the monte-carlo sampling occurs for all parameters
including non-informative ETAs. A fix ensure that non-informative
etas in saem are fixed to zero while sampling the phi values.
This may change results for models with uninformative etas. To
ignore the uninformative etas with saem you ca use use the prior
saem handling with saemControl(handleUninformativeEtas=FALSE).
Gracefully degrade when $cov is not in the right form (see #423)
Add support for PopED in place solving (used in babelmixr2)
If est=foceiControl() or other nlmixr2 control with the class
foceiControl infer the estimation method is focei
Add back the warnings when estimation methods ignore the boundaries
When using rxSolve, now respects the values from tableControl()
(#465 and #297)
lotri and import
them via function pointersfocei cache needs to be based on the parameter order as well as
the model information (#415)Algebraic mu referencing has been implemented in nlme and saem.
New estimation method "nlm" has been added to estimate population
only likelihoods using stats::nlm and possibly return a
standardized nlmixr2 fit.
New estimation method "nls" has been added to estimate population
only problems. This uses minpack.lm::nlsNM by default if
present, or the stats::nls
New estimation method "optim" has been added to estimate population
only likelihoods. This uses stats::optim and returns a
standardized nlmixr2 fit.
New estimation method "nlminb" has been added to estimate population
only likelihoods. This uses stats::nlminb and returns a
standardized nlmixr2 fit.
New estimation methods from the minqa package: "bobyqa", "uobyqa"
and "newuoa" have been added to estimate population only
likelihoods. These methods returns a standardized nlmixr2 fit.
New estimation method "lbfgsb3c" to estimate population only
likelihoods. This returns a standardized nlmixr2 fit.
New estimation method "n1qn1" to estimate population only
likelihoods. This returns a standardized nlmixr2 fit.
Added new feature for vpcSim() where a minimum number of subjects
are simulated from the model when trying to fill in ODEs that were
not solved successfully. By default this is 10. This also
works-around a bug when there is only one subject simulated and the
data.frame has a slightly different output.
Removed fit$saemTransformedData since it isn't actually used in
saem anymore (but will break anyone's code who is using it)
Now the internal function .foceiPreProcessData() requires the
rxode2 control rxControl() because some of the new steady state
lag features need to translate the data differently based on
rxControl() options.
Printing models with correlated omega values and omega values fixed to zero no longer fails (#359)
Add back values for $parHistData (#368)
This requires a new rxode2 which will fix multiple endpoint issues observed (#394)
Manual back-transformed values in $parFixed are now displaying
correctly and are calculated based on the confidence interval in the
control instead of 95% confidence no matter what (#397)
as.rxUi() method was added for fit models (#377)nlmixr2 models will crash R.As requested by CRAN, remove Rvmmin
Values in $parFixed for BSV without exponential transformation are now
correctly shown (#366)
rxode2 now allows simulation with omega having diagonal
zero elements, $omega and $omegaR now reflects this information
including the zero omega elements in the output. On the other hand,
the other eta-information and standard error information for zero
etas are still excluded in $phiR, $phiSE, $eta etc.vpcSim() works when an eta value is fixed to 0 (#341)
augPred() now consistently uses the simulation model (instead of
the inner model used for CWRES calculation).
ucminfAdd $fitMergeFull, $fitMergInner, $fitMergeLeft,
$fitMergeRight as a complement to $dataMergeFull,
$dataMergInner, $dataMergeLeft, $dataMergeRight. The fit
variants prefer columns in the fit dataset instead of the original
dataset. This is useful for goodness of fit plots with censoring
since the DV in the fit simulates values under the ipred/residual
assumption and will give more appropriate goodness of fits,
otherwise these values are the limit of whatever censoring is
applied
Moved the mu reference fix for the split mu referenced model here (from babelmixr2)
Breaking change, now calculate condition number based on covariance
and correlation, the names have changed to be more explicit.
conditionNumber changed to conditionNumberCov and a new metric
conditionNumberCor has been added.
A bug in boundary value detection prevented automatic covariance calculation with FOCEi estimation (#318)
Fix vpcSim so that it will be a bit more robust when it is
difficult to simulate.
A bug in model piping which did not allow models to be appended to was fixed (rxode2#364)
An internal change was made in nlmixr2.rxUi() to better support the
babelmixr2 PKNCA estimation method (babelmixr2#75)
Fixed bug where $iniUi did not return the initial ui when running
non focei related methods. Also added alias of $uiIni to the
same function.
Dropped Stan headers for this package, also updated to C++17
Allows $etaH and related family to be integrated into a saem fit
if cwres is calculated.
Fixed a bug where nlmixrLlikObs in the merged dataset is sometimes
named llikObs, now it is always named nlmixrLlikObs
Fixed a bug where nlmixrLlikObs shows up in merged dataset when
cwres is not calculated (it was always 0), also allow cwres
calculation to pick up nlmixrLlikObs in merged dataset.
Dropped dparser dependency
Fixes $etaH memory corruption so the standard errors of etas are now correct
Removed the memory requirements for focei by neta*neta*nsub
Fixed character based covariates so the work correctly (again) with focei. Added a test for this as well.
Fixes $dataMergeInner so that observation-based log-likelihoods
work with infusions. Should fix tests with ggPMX
Fixes $etaSE and $etaRSE to work correctly when there is only 1
eta.
Fixes npde valgrind observed on CRAN machines
Gill forward differences will not repeat now (by default), You can
change back to prior behavior with foceiControl(repeatGillMax=3)
Number of sticky recalculation is reduced to 4; to have the old
behavior use foceiControl(stickyRecalcN=5)
n2ll has been changed to ll to specify individual
log-likelihoods. This was only used in simulation and was not well
documented.
Generalized log-likelihood is only supported with rxode2 2.0.8 or later.
The S matrix calculation was made a bit more robust to errors in
individual gradients. When there are errors in the individual
gradient calculation, assume the gradient is the same as the
overall gradient. In the tests cases, were reasonable using this
adjusted S matrix. This means if some individuals do not have very
much data to support a specific parameter, a S matrix calculation
for the population will still be generated. When there is some
patients/subject combinations that do not have sufficient data, we
will add the following to the run information: S matrix had problems solving for some subject and parameters. The S matrix
calculation will still fail if the percentage of parameters that
are being reset is lower than foceiControl(smatPer=0.6) or
whatever you specify.
The r,s covariance matrix will now also check for unreasonably
small values (controlled by foceiControl(covSmall=...)) and
select a different covariance estimate method even when the "r" and
"s" matrices are calculated "correctly".
What type(s) censoring (if any) is now stored in fit$censInformation
Standard errors of $etas can now be obtained with fit$phiSE,
also available are fit$phiRSE (relative standard error),
fit$phiH, (individual hessian), fit$phiC (individual
covariances), fit$phiR (individual correlation matrices)
Can also use Shi 2021 differences in addition to Gill differences. In our tests (using the same datasets as CPT) these produced worse estimates than the Gill 1983, though it is unclear why since it should be a faster more accurate method. A modified version is used in calculating the individual Hessians of numerically for the generalized likelihood approach.
Generalized likelihood estimation is now present in nlmixr2est for
focei, foce and posthoc
nmNearPD() is a function you may use for nearest positive definite
matrix. This is derived from Matrix::nearPD() but is implemented
in C/C++ to be used in (possibly threaded) optimization.
Individual Hessians can be accessed by $phiH, covariance by
$phiC, eta standard errors by $phiSE and eta RSEs can be
accessed by $phiRSE. There are eta aliases for these as well
($etaH, $etaC, $etaSE, and $etaRSE).
Can now access the individual point's contribution to the overall
likelihood when merging to the original dataset. These merges can be
accessed with $dataMergeFull, $dataMergeLeft, $dataMergeRight,
and $dataMergeInner. The columns with the individual data column
is nlmixrLlikObs.
To calculate the total focei/foce objective function, the sum of the
likelihoods still need to be adjusted by the omega/eta contribution,
and the individual Hessians, and possibly the NONMEM objective
function offset constant.
cens and limit do not
produce the correct table output (#180)bobyqa
by default. With this, it is more important to examine the model
parameters and fits for plausibility.pd/npd as an output as well as npd/npdenlmixr2 "saem" fit from another R session,
nlmixr2 will no longer crash with fit$objfNPDE was identical to NPD even with correlated models, this was
fixed (prior output was actually NPDE).FOCEi censoring fixes:
SAEM Censoring fixes:
Censoring handling was unified
Added ui$getSplitMuModel which is used in babelmixr2 and will be
used in the refined stepwise covariate selection of nlmixr2extra
Added work-around to remove _nlmixr2est_RcppExport_registerCCallable
since the registering of C callable are handled manually at the moment.
Use .zeros() for the matrices in armadillo in addition to relying
on calloc to give zero matrices.
Fixed one uninitialized object
Fix for augPred so it works on population only models
nlme no longer sets options to treat all covariates as non
mu-referenced covariates, but directly calls a function that can
turn on or off the mu-reference covariate selection.
vpcSim now tries to simulate IDs that didn't simulate correctly (with a warning)
Export nmObjHandleControlObject
nlmixr2est contains the estimation functions within nlmixr2.
Remove lower level foceiFit function. Focei, foce, fo, foi, and
posthoc now directly takes rxode2 ui objects
New error types are supported in focei including mixing theta and etas in residual errors and different types of proportional errors
Different types of additive and proportional errors can be used for
each endpoint using + combined1() or + combined2() otherwise it
takes the supplied addProp option to figure out which type of
combined model is run (by default combined2())
Focei model cache is now named focei-md5Digest.qs and uses qs
compression/saving/loading.
foceiControl() aligned between other methods.
foceiControl(adjLik=TRUE) uses the NONMEM-style objective function
throughout. foceiControl(adjLik=FALSE) uses the adjusted
objective function throughout, and adjusts it back to the NONMEM
objective function.
Lag time and other between subject variability differences no longer calculate an ideal relative step size, but an absolute step size when using Gill differences (default)
Objective function checks for infinite/NaN/NA values for the entire solving space and ensures no overflow occurs when calculating the inner hessian
mu referencing is no longer required for saem; Internally non
mu-referenced values are converted to mu referenced values and the
converted back when calculating the nlmixr2 object.
nlmixr2 forced the parameter ordering to (1) population effects,
(2) non mu-referenced between subject effects (3) omega estimates
and (4) residual effects. This changes the order that nlmixr2 sees
the parameters. Since this is based on a random number generator,
the optimization trajectory will be different and have different
results than nlmixr
Components of omega can now be fixed.
Residual error components can also be fixed.
When optimizing only one residual value, nlmixr2's saem uses nlm
from R, which is more efficient than the nealder-meade method.
Lower level saem functions (like configsaem()) are not exported
because they are increasingly difficult to use and convert to
something standard; a few methods (like print, summary etc) are
maintained to view the lower level object and for debugging it.
Parameter history and print-out no longer includes fixed parameters.
The model to calculate the residuals more closely matches the model used for estimation to remove small rounding differences that may occur in the models.
Different types of additive and proportional errors can be used for
each endpoint using + combined1() or + combined2() otherwise it
takes the supplied addProp option to figure out which type of
combined model is run (by default combined2())
Parameter history and printout now uses standard deviation for additive only components, matching the estimation of the components.
rxode2 solving options are now saved in the rxControl part of
the saemControl(). That is
saemControl(rxControl=rxControl(...)); This fixes any conflicting
option names as well as allowing alignment between the control
structures in focei, nlme and saem
saemControl() aligned between other methods.
nlme has been completely rewritten to directly run from the
rxode2 UI
nlme always tries to use mu-referencing (when available)
Internally nlme now uses parallel processing for solving so it
should be faster.
nlmixr2NlmeControl() (which will overwrite nlmeControl())
documents and adds more options to nlme. Also aligned with other
methods.
weights, fixed, random can be specified in
nlmixr2NlmeControl(). If so, then the nlme object will be
returned.
returnNlme is a new option that will return the nlme object
instead of the traditional nlme object.
nlme_ode and lme_lin_cmpt are both removed.
rxode2 solving options are now saved in the rxControl part of
the saemControl(). That is
nlmeControl(rxControl=rxControl(...)); This fixes any conflicting
option names as well as allowing alignment between the control
structures in focei, nlme and saem
With saem, the nlmixr2 function now saves/compresses the phiM
information. This means the gaussian and Laplacians likelihoods can
be calculated when you save the nlmixr object and then restore it
later.
The nlmixr2 object compresses infrequently used and removes many
unneeded objects. Even with compression, the saem objects are
often a bit bigger since they include the large phiM object.
nlmixr2 now supports non-mu referenced ETAs in the fit$parFixed
and fit$parFixedDf
nlmixr2 interface changed to use rxode2 UI
keep and drop are added to tableControl to influence the end data-frame
$simInfo uses a quoted expression for $rx instead of a string
$simInfo$sigma is a diagonal matrix since now the normal
simulation is controlled by the variability modeled as a population
value.
nlmixr2 now allows etas that have initial omega estimates of zero
to be dropped from the model (instead of issuing an error about a
non-positive definite $omega matrix)
addNpde(fit, table=tableControl(nsim=500))vpc function rewritten and split out to vpcSim() and
vpcPlot() (which is a replacement for vpc()).
There were too many mismatches between vpc::vpc and nlmixr::vpc
which caused inconsistencies in code based on load order of vpc
and nlmixr. This way both coexist, and you can use the vpc
simulation for other packages more easily (like ggPMX) without
creating or summarizing data since ggPMX has its own methods for
summarizing and creating plots.
VPC now directly uses rxode2::rxSolve
augPred() has been written to use the new fit object.
nlmixr2AugPred was changed to nlmixr2AugPredSolve()
augPred uses the new interface and supports multiple endpoints.
The endpoint name is now always on the plot(augPred(fit)).
fit$est, and now
getFitMethod(fit) simply returns fit$estMany methods lower level utility functions have been deleted.
nmDocx, nmLst and nmSave have been removed.
function 'rx_0ba247452048de33b1ffb8af516714fc__calc_lhs' not provided by package 'rx_0ba247452048de33b1ffb8af516714fc_' would cause the
estimation to stop. Now rxode2::rxClean() is run when this occurs.