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`

- Align with the possibility that linCmt sensitivities may not be present (like intel c++)

`focei`

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)

- An
`as.rxUi()`

method was added for fit models (#377)

- Version bump and a minor documentation update (same as nlmixr2est 2.1.7). This version bump is to simply allow correct binary linkage to rxode2 2.0.14. Otherwise
`nlmixr2`

models will crash R.

As requested by CRAN, remove

`Rvmmin`

Values in

`$parFixed`

for BSV without exponential transformation are now correctly shown (#366)

- Since
`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).

- Dropped dependence on orphaned package
`ucminf`

Add

`$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 appliedMoved 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 correctRemoved 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.

- Fixed bug where datasets with censoring that are not lower case
`cens`

and`limit`

do not produce the correct table output (#180)

- Resets now scale properly when a value is simulated outside the limit
- Models with zero gradients on the first step now switch to
`bobyqa`

by default. With this, it is more important to examine the model parameters and fits for plausibility.

- Add
`pd`

/`npd`

as an output as well as`npd`

/`npde`

- When loading a
`nlmixr2`

“saem” fit from another R session,`nlmixr2`

will no longer crash with`fit$objf`

`NPDE`

was identical to`NPD`

even with correlated models, this was fixed (prior output was actually`NPDE`

).

- FOCEi censoring fixes:
- M4 method equation bug fix
- M4 method derivative change based on equation fix
- M2 method added missing derivative
- Censoring already dTBS

- SAEM Censoring fixes:
- SAEM method M4 method equation bug fix
- Censoring limit changed to dTBS

- 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 objectsNew 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,- 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`

- non mu-referenced between subject effects (3) omega estimates and (4) residual effects. This changes the order that
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)

- Fixed a bug where the number of simulations for a NPDE calculation are correctly passed by
`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))`

.

- Internally, fit estimation method is saved in
`fit$est`

, and now`getFitMethod(fit)`

simply returns`fit$est`

Many methods lower level utility functions have been deleted.

`nmDocx`

,`nmLst`

and`nmSave`

have been removed.

- Now will reset the cache when items cannot be loaded. In the past error messages like
`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.