`rxUi`

compression now defaults to fast compressionFixes String literal formatting issues as identified by CRAN (#643)

Removes linear compartment solutions with gradients for intel c++ compiler (since they crash the compiler).

Steady state with lag times are no longer shifted by the lag time and then solved to steady state by default. In addition the steady state at the original time of dosing is also back-calculated. If you want the old behavior you can bring back the option with

`ssAtDoseTime=FALSE`

.“dop853” now uses the

`hmax`

/`h0`

values from the`rxControl()`

or`rxSolve()`

. This may change some ODE solving using “dop853”When not specified (and xgxr is available), the x axis is no longer assumed to be in hours

User defined functions can now be R functions. For many of these R functions they can be converted to C with

`rxFun()`

(you can see the C code afterwards with`rxC("funName")`

)Parallel solving of models that require sorting (like modeled lag times, modeled duration etc) now solve in parallel instead of downgrading to single threaded solving

Steady state infusions with a duration of infusions greater than the inter-dose interval are now supported.

Added

`$symengineModelNoPrune`

and`$symengineModelPrune`

for loading models into rxode2 with`rxS()`

When plotting and creating confidence intervals for multiple endpoint models simulated from a rxode2 ui model, you can plot/summarize each endpoint with

`sim`

. (ie.`confint(model, "sim")`

or`plot(model, sim)`

).If you only want to summarize a subset of endpoints, you can focus on the endpoint by pre-pending the endpoint with

`sim.`

For example if you wanted to plot/summarize only the endpoint`eff`

you would use`sim.eff`

. (ie`confint(model, "sim.eff")`

or`plot(model, sim.eff)`

)Added

`model$simulationIniModel`

which prepend the initial conditions in the`ini({})`

block to the classic`rxode2({})`

model.Now

`model$simulationModel`

and`model$simulationIniModel`

will save and use the initialization values from the compiled model, and will solve as if it was the original ui model.Allow

`ini(model) <- NULL`

to drop ini block and`as.ini(NULL)`

gives`ini({})`

(Issue #523)Add a function

`modelExtract()`

to extract model lines to allow modifying them and then changing the model by piping or simply assigning the modified lines with`model(ui) <- newModifiedLines`

Add Algebraic mu-referencing detection (mu2) that allows you to express mu-referenced covariates as:

Instead of the

That was previously required (where `log.WT.div.70.5`

was calculated in the data) for mu expressions. The `ui`

now has more information to allow transformation of data internally and transformation to the old mu-referencing style to run the optimization.

Allow steady state infusions with a duration of infusion greater than the inter-dose interval to be solved.

Solves will now possibly print more information when issuing a “could not solve the system” error

The function

`rxSetPipingAuto()`

is now exported to change the way you affect piping in your individual setupAllow covariates to be specified in the model piping, that is

`mod %>% model(a=var+3, cov="var")`

will add`"var"`

as a covariate.When calculating confidence intervals for

`rxode2`

simulated objects you can now use`by`

to stratify the simulation summary. For example you can now stratify by gender and race by:`confint(sim, "sim", by=c("race", "gender"))`

When calculating the intervals for

`rxode2`

simulated objects you can now use`ci=FALSE`

so that it only calculates the default intervals without bands on each of the percentiles; You can also choose not to match the secondary bands limits with`levels`

but use your own`ci=0.99`

for instanceA new function was introduced

`meanProbs()`

which calculates the mean and expected confidence bands under either the normal or t distributionA related new function was introduced that calculates the mean and confidence bands under the Bernoulli/Binomial distribution (

`binomProbs()`

)When calculating the intervals for

`rxode2`

simulated objects you can also use`mean=TRUE`

to use the mean for the first level of confidence using`meanProbs()`

. For this confidence interval you can override the`n`

used in the confidence interval by using`n=#`

. You can also change this to a prediction interval instead using`pred=TRUE`

.Also when calculating the intervals for

`rxode2`

simulated object you can also use`mean="binom"`

to use the binomial distributional information (and ci) for the first level of confidence using`binomProbs()`

. For this confidence interval you can override the`n`

used in the confidence interval by using`n=#`

. You can also change this to a prediction interval instead using`pred=TRUE`

. With`pred=TRUE`

you can override the number of predicted samples with`m=#`

When plotting the

`confint`

derived intervals from an`rxode2`

simulation, you can now subset based on a simulated value like`plot(ci, Cc)`

which will only plot the variable`Cc`

that you summarized even if you also summarized`eff`

(for instance).When the rxode2 ui is a compressed ui object, you can modify the ini block with

`$ini <-`

or modify the model block with`$model <-`

. These are equivalent to`ini(model) <-`

and`model(model) <-`

, respectively. Otherwise, the object is added to the user defined components in the function (ie`$meta`

). When the object is uncompressed, it simply assigns it to the environment instead (just like before).When printing meta information that happens to be a

`lotri`

compatible matrix, use`lotri`

to express it instead of the default R expression.Allow character vectors to be converted to expressions for piping (#552)

`rxAppendModel()`

will now take an arbitrary number of models and append them together; It also has better handling of models with duplicate parameters and models without`ini()`

blocks (#617 / #573 / #575).`keep`

will now also keep attributes of the input data (with special handling for`levels`

); This means a broader variety of classes will be kept carrying more information with it (for example ordered factors, data frame columns with unit information, etc)Piping arguments

`append`

for`ini()`

and`model()`

have been aligned to perform similarly. Therefore`ini(append=)`

now can take expressions instead of simply strings and`model(append=)`

can also take strings. Also model piping now can specify the integer line number to be modified just like the`ini()`

could. Also`model(append=FALSE)`

has been changed to`model(append=NULL)`

. While the behavior is the same when you don’t specify the argument, the behavior has changed to align with`ini()`

when piping. Hence`model(append=TRUE)`

will append and`model(append=FALSE)`

will now pre-pend to the model.`model(append=NULL)`

will modify lines like the behavior of`ini(append=NULL)`

. The default of`model(line)`

modifying a line in-place still applies. While this is a breaking change, most code will perform the same.Labels can now be dropped by

`ini(param=label(NULL))`

. Also parameters can be dropped with the idiom`model(param=NULL)`

or`ini(param=NULL)`

changes the parameter to a covariate to align with this idiom of dropping parameters`rxRename`

has been refactored to run faster

Add

`as.model()`

for list expressions, which implies`model(ui) <- ui$lstExpr`

will assign model components. It will also more robustly work with character vectorsSimulated objects from

`rxSolve`

now can access the model variables with`$rxModelVars`

Simulation models from the UI now use

`rxerr.endpoint`

instead of`err.endpoint`

for the`sigma`

residual error. This is to align with the convention that internally generated variables start with`rx`

or`nlmixr`

Sorting only uses timsort now, and was upgraded to the latest version from Morwenn

Simulating/solving from functions/ui now prefers params over

`omega`

and`sigma`

in the model (#632)Piping does not add constants to the initial estimates

When constants are specified in the

`model({})`

block (like`k <- 1`

), they will not be to the`ini`

blockBug fix for

`geom_amt()`

when the`aes`

transformation has`x`

Bug fix for some covariate updates that may affect multiple compartment models (like issue #581)

- Modify plot code to work with development
`xgxr`

CRAN requested that FORTRAN

`kind`

be changed as it was not portable; This was commented code, and simply removed the comment.Bug-fix for

`geom_amt()`

; also now uses`linewidth`

and at least`ggplot2 3.4.0`

Some documentation was cleaned up from

`rxode2`

2.0.13

A bug was fixed so that the

`zeroRe()`

function works with correlated omega values.A bug was fixed so that the

`rename()`

function works with initial conditions for compartments (`cmt(0)`

)

A new function

`zeroRe()`

allows simple setting of omega and/or sigma values to zero for a model (#456)Diagonal zeros in the

`omega`

and`sigma`

matrices are treated as zeros in the model. The corresponding`omega`

and`sigma`

matrices drop columns/rows where the diagonals are zero to create a new`omega`

and`sigma`

matrix for simulation. This is the same idiom that NONMEM uses for simulation from these matrices.Add the ability to pipe model estimates from another model by

`parentModel %>% ini(modelWithNewEsts)`

Add the ability to append model statements with piping using

`%>% model(x=3, append=d/dt(depot))`

, still supports appending with`append=TRUE`

and pre-pending with`append=NA`

(the default is to replace lines with`append=FALSE`

)rxSolve’s keep argument will now maintain character and factor classes from input data with the same class (#190)

Parameter labels may now be modified via

`ini(param = label("text"))`

(#351).Parameter order may be modified via the

`append`

argument to`ini()`

when piping a model. For example,`ini(param = 1, append = 0)`

or`ini(param = label("text"), append = "param2")`

(#352).

If lower/upper bounds are outside the required bounds, the adjustment is displayed.

When initial values are piped that break the model’s boundary condition reset the boundary to unbounded and message which boundary was reset.

Added

`as.rxUi()`

function to convert the following objects to`rxUi`

objects:`rxode2`

,`rxModelVars`

,`function`

. Converting nlmixr2 fits to`rxUi`

will be placed in the`s3`

method in the corresponding package.`assertRxUi(x)`

now uses`as.rxUi()`

so that it can be extended outside of`rxode2`

/`nlmixr2`

.`rxode2`

now supports`addl`

with`ss`

dosesMoved

`rxDerived`

to`rxode2parse`

(and re-exported it here).Added test for transit compartment solving in absence of dosing to the transit compartment (fixed in

`rxode2parse`

but solving tested here)Using

`ini()`

without any arguments on a`rxode2`

type function will return the`ini()`

block. Also added a method`ini(mod) <- iniBlock`

to modify the`ini`

block is you wish.`iniBlock`

should be an expression.Using

`model()`

without any arguments on a`rxode2`

type function will return the`model()`

block. Also added a new method`model(mod) <- modelBlock`

Added a new method

`rxode2(mod) <- modFunction`

which allows replacing the function with a new function while maintaining the meta information about the ui (like information that comes from`nonmem2rx`

models). The`modFunction`

should be the body of the new function, the new function, or a new`rxode2`

ui.`rxode2`

ui objects now have a`$sticky`

item inside the internal (compressed) environment. This`$sticky`

tells what variables to keep if there is a “significant” change in the ui during piping or other sort of model change. This is respected during model piping, or modifying the model with`ini(mod)<-`

,`model(mod)<-`

,`rxode2(mod)<-`

. A significant change is a change in the model block, a change in the number of estimates, or a change to the value of the estimates. Estimate bounds, weather an estimate is fixed or estimate label changes are not considered significant.Added

`as.ini()`

method to convert various formats to an ini expression. It is used internally with`ini(mod)<-`

. If you want to assign something new that you can convert to an ini expression, add a method for`as.ini()`

.Added

`as.model()`

method to convert various formats to a model expression. It is used internally with`model(mod)<-`

. If you want to assign something new that you can convert to a model expression, add a method for`as.model()`

.

Give a more meaningful error for ‘rxode2’ ui models with only error expressions

Break the ABI requirement between

`roxde2()`

and`rxode2parse()`

The new

`rxode2parse`

will fix the`sprintf`

exclusion shown on CRAN.

Time invariant covariates can now contain ‘NA’ values.

When a column has ‘NA’ for the entire id, now ‘rxode2’ warns about both the id and column instead of just the id.

To fix some CRAN issues in ‘nlmixr2est’, make the version dependency explicit.

Remove log likelihoods from ‘rxode2’ to reduce compilation time and increase maintainability of ‘rxode2’. They were transferred to ‘rxode2ll’ (requested by CRAN).

Remove the parsing from ‘rxode2’ and solved linear compartment code and move to ‘rxode2parse’ to reduce the compilation time (as requested by CRAN).

Remove the random number generation from ‘rxode2’ and move to ‘rxode2random’ to reduce the compilation time (as requested by CRAN).

Remove the event table translation and generation from ‘rxode2’ and move to ‘rxode2et’ to reduce the compilation time (as requested by CRAN).

Change the

`rxode2`

ui object so it is a compressed, serialized object by default. This could reduce the`C stack size`

problem that occurs with too many environments in R.Warn when ignoring items during simulations

Export a method to change ‘rxode2’ solve methods into internal integers

Bug fix for time invariant covariates identified as time variant covariate when the individual’s time starts after

`0`

.

`rxgamma`

now only allows a`rate`

input. This aligns with the internal`rxode2`

version of`rxgamma`

and clarifies how this will be used. It is also aligned with the`llikGamma`

function used for generalized likelihood estimation.ui

`cauchy`

simulations now follow the ui for`normal`

and`t`

distributions, which means you can combine with transformations. This is because the`cauchy`

is a`t`

distribution with one degree of freedom.ui

`dnorm()`

and`norm()`

are no longer equivalent to`add()`

. Now it allows you to use the loglik`llikNorm()`

instead of the standard`nlmixr2`

style focei likelihood. This is done by adding`dnorm()`

at the end of the line. It also means`dnorm()`

now doesn’t take any arguments.Vandercorput normal removed (non-random number generator)

Allow models in the

`nlmixr2`

form without an`ini({})`

blockAllow model piping of an omega matrix by

`f %>% ini(omegaMatrix)`

Standard models created with

`rxode2()`

can no be piped into a model functionFamilies of log-likelihood were added to

`rxode2`

so that mixed likelihood nonlinear mixed effects models may be specified and run.The memory footprint of a

`rxode2`

solving has been reducedPiping now allow named strings (issue #249)

`rxode2`

’s symengine would convert`sqrt(2)`

to`M_SQRT_2`

when it should be`M_SQRT2`

. This has been fixed; it was most noticeable in nlmixr2 log-likelihood estimation methods`rxode2`

treats`DV`

as a non-covariate with`etTran`

(last time it would duplicate if it is in the model). This is most noticeable in the nlmixr2 log-likelihood estimation methods.

A new flag (

`rxFlag`

) has been created to tell you where in the`rxode2`

solving process you are. This is useful for debugging. If outputting this variable it will always be`11`

or calculating the left handed equations. If you are using in conjunction with the`printf()`

methods, it is a double variable and should be formatted with`"%f"`

.An additional option of

`fullPrint`

has been added to`rxode2()`

which allows`rprintf()`

to be used in almost all of`rxode2()`

steps (inductive linearization and matrix exponential are the exception here) instead of just the integration`ddt`

step. It defaults to`FALSE`

.

Removed accidental

`^S`

from news as requested by CRAN.Bug fix for more complicated mu-referencing.

Change rxode2 md5 to only depend on the C/C++/Fortran code and headers not the R files. That way if there is binary compatibility between

`nlmixr2est`

and`rxode2`

, a new version of`nlmixr2est`

will not need to be submitted to CRAN.

The options for

`rxControl`

and`rxSolve`

are more strict.`camelCase`

is now always used. Old options like`add.cov`

and`transit_abs`

are no longer supported, only`addCov`

is supported.A new option,

`sigdig`

has been added to`rxControl()`

, which controls some of the more common significant figure options like`atol`

,`rtol`

,`ssAtol`

,`ssRtol`

, with a single option.

For simulations,

`$simulationSigma`

now assumes a diagonal matrix. The sigma values are assumed to be standard normal, and uncorrelated between endpoints. Simulation with uncertainty will still draw from this identity diagonal matrixParallel solving now seeds each simulation per each individual based on the initial seed plus the simulation id. This makes the simulation reproducible regardless of the number of cores running the simulation.

Solved objects now access the underlying rxode model with

`$rxode2`

instead of`$rxode`

Since this change names,

`rxode2`

,`rxode`

and`RxODE`

all perform the same function.Options were changed from

`RxODE.syntax`

to`rxode2.syntax`

.Assigning states with

`rxode2.syntax.assign.state`

(was`RxODE.syntax.assign.state`

) is no longer supported.Enforcing “pure” assignment syntax with

`=`

syntax is no longer supported so`rxode2.syntax.assign`

is no longer supported (was`RxODE.syntax.assign`

).Since R supports

`**`

as an exponentiation operator, the pure syntax without`**`

can no longer be enabled. Hence`rxode2.syntax.star.pow`

(was`RxODE.syntax.star.pow`

) no longer has any effect.The “pure” syntax that requires a semicolon can no longer be enabled. Therefore

`rxode2.syntax.require.semicolon`

(was`RxODE.syntax.require.semicolon`

) no longer has any effect.The syntax

`state(0)`

can no longer be turned off.`rxode2.syntax.allow.ini0`

(was`RxODE.syntax.allow.ini0`

) has been removed.Variable with dots in variable and state names like

`state.name`

works in R. Therefore, “pure” syntax of excluding`.`

values from variables cannot be enforced with`rxode2.syntax.allow.dots`

(was`RxODE.syntax.allow.dots`

).The mnemonic

`et(rate=model)`

and`et(dur=model)`

mnemonics have been removed.`rate`

needs to be set to`-1`

and`-2`

manually instead.The function

`rxode2Test()`

has been removed in favor of using testthat directly.Transit compartments need to use a new

`evid`

,`evid=7`

. That being said, the`transitAbs`

option is no longer supported.`ID`

columns in input parameter data frames are not sorted or merged with original dataset any more; The underlying assumption of ID order should now be checked outside of`rxode2()`

. Note that the event data frame is still sorted.

The UI functions of

`nlmixr`

have been ported to work in`rxode2`

directly.`rxModelVars({})`

is now supported.You may now combine 2 models in

`rxode2`

with`rxAppendModel()`

. In fact, as long as the first value is a rxode2 evaluated ui model, you can use`c`

/`rbind`

to bind 2 or more models together.You may now append model lines with piping using

`%>% model(lines, append=TRUE)`

you can also pre-pend lines by`%>% model(lines, append=NA)`

You may now rename model variables, states and defined parameters with

`%>% rxRename(new=old)`

or if`dplyr`

is loaded:`%>% rename(new=old)`

You can fix parameters with

`%>% ini(tcl=fix)`

or`%>% ini(fix(tcl))`

as well as unfix parameters with`%>% ini(tcl=unfix)`

or`%>% ini(unfix(tcl))`

Strict R headers are enforced more places

Since there are many changes that could be incompatible, this version has been renamed to

`rxode2`

`rxode2()`

printout no longer uses rules and centered headings to make it display better on a larger variety of systems.

`tad()`

and related time features only reset at the start of an infusion (as opposed to starting at the beginning and end of an infusion)

- Change handling of missing covariates while interpolating “nocb” so that the time-varying covariates use “nocb” interpolation (#469)

Fix subject initialization of

`focei`

problem (#464)Fix LHS offset to allow internal threading and more parallel processing in the future.

Remove warnings for duration and rate

Don’t export pillar methods any more (simply register at load if present)

As requested by CRAN, change fortran and C binding for BLAS an LINPACK

Fix the LTO issue that CRAN identified.

Move the omp files so they come first to support clang13, as identified by CRAN.

For now, be a little more conservative in

`dur()`

and`rate()`

warnings because`linCmt()`

models in`nlmixr`

currently produce irrelevant warnings.

Always calculate “nolhs” for using numeric differences when the inner problem. This allows the inner problem to fallback to a finite difference approximation to the focei objective function.

Updated the parser C code grammar using latest dparser CRAN package

Added a new cbind function that is used to mix data frame input with simulated individual parameters and residual parameters,

`rxCbindStudyIndividual()`

.Now data frame input can be mixed with simulating from omega and sigma matrices (though not yet in nested simulations)

Race conditions when simulating random numbers is solved by chunking each simulation into groups that will always be performed per each thread. This way the simulation is now reproducible regardless of load. Because of the chunking, simulations with random numbers generated inside of it are now threaded by default (though a warning is produced about the simulation only be reproducible when run with the same number of threads)

Simulations were double checked and made sure to use the engine reserved for each core run in parallel; Some of the random generators were not taking random numbers from the correct engine, which was corrected. Therefore, simulations from this version are expected to be different (in parallel) than previous versions.

Added function

`rxSetSeed()`

to set the internal RxODE seed instead of grabbing it from a uniform random number tied to the original R seed. This will avoid the possibility of duplicate seeds and is the best practice.Updating parameter pointers is done once per ID and locked based on ID to remove the recursion in #399, but still have the correct behavior see #430

Parsing updated to retain “param()” in normalized model, #432.

Handle edge case of interpolation at first index correctly, fixes #433

Instead of storing each dose information sequentially, store dose information at the same index of the

`evid`

defining the dose. This memory rewrite is to fix the issue #435.Start using strict headers as it is required for the forthcoming release of

`Rcpp`

. Thanks to Dirk Eddelbuettel for some of the fixes and alerting us to this change.Check arguments for

`add.dosing()`

more strictly. See Issue #441Issue a warning when either

`dur()`

or`rate()`

is in the model but the modeled rate and duration is not included in the event table.When the data requires a modeled rate and modeled duration but it is not in the model, warn about the mismatch in data

Added a back-door for debugging. If you specify

`options(RxODE.debug=TRUE)`

then each solve saves the solving information to the file`"last-rxode.qs"`

before actually solving the system.Only will try to solve RxODE problems on compatible models; If the model is not supported it will throw an error instead of crashing (See #449)

Turn off parallel ODE solving whenever the system needs to sort times based on model dosing. Currently this type of solving is not thread safe.

Update timsort headers to latest version.

At the request of CRAN, stripping the debugging symbols for the CRAN release is no longer performed. This means a larger binary size for RxODE in this release.

At the request of CRAN the

`liblsoda`

code has been changed so that the memory in C defined by`_C()`

is now defined by`_rxC()`

. This will be seen in some of the error messages, which will no longer match the error messages of unmodified liblsoda.`iCov`

behavior has shifted to merge on the input event dataset. See Issue #409; This is more in line with expectations of`iCov`

behavior, and reduces the amount of code needed to maintain`iCov`

.The

`iCov`

in the pipeline is no longer supported because it simply is a merge with the event dataset.This can be a breaking change depending on the code you use. Note that clinical trial simulations, resampling is likely better than trying to fill out

`iCov`

for every individual which was the prior use.Bug fix for crashes with string covariates or factor covariates, issue #410. Also factor column names are compared with case insensitivity just like the rest of the column names for event tables or data sets in

`RxODE`

.

- Fix issue #399

Change syntax vignette to use markdown option

`screenshot.force=FALSE`

. This should get rid of the`webshot`

errorChange to depend on dparser 1.3.0, which has some memory fixes

RxODE imports but does not link to

`checkmate`

any longer. This change should make recompilation of RxODE to work with different releases of`checkmate`

unnecessary.Default Solaris solver changed back to “lsoda”

Fix Bug #393, where in certain circumstances

`rxSolve(...,theta=)`

did not solve for all subjects.Will not ignore NEWS and README when building the package so that they will show up on CRAN. You can also access the news by

`news(package="RxODE")`

Changed

`ODR`

model names from time id to`_rx`

followed by the`md5`

hash id and a per-session counter id; For packages the id is`_rxp`

followed by the`md5`

hash and a per-session counter id.Changed

`qs`

to be more conservative in hash creation. Add a check hash as well as NOT using altrep stringfish representation.

Maintenance release – use

`std::floor`

and cast variables to`double`

for internal C functions. This should allow a successful compile on Solaris CRAN.Changed

`units`

from an Imports to a Suggests to allow testing on Solaris rhubChanged

`ODR`

model names from time id to`_rx`

followed by the`md5`

hash id; For packages the id is`_rxp`

followed by the`md5`

hash.Removed AD linear compartment solutions for Windows R 3.6, though they still work for Windows R 4.0 (You can get them back for Windows R 3.6 if you install

`BH`

1.66.0-1 and then recompile from source).- This will cause
`nlmixr`

to fail with solved systems on Windows 3.6. Currently the Stan Headers do not compile on this system so they are disabled at this time.

- This will cause
RxODE imports but does not link to

`qs`

any longer; This change should make recompilation of RxODE to work with different releases of`qs`

unnecessary.RxODE now checks for binary compatibility for

`Rcpp`

,`dparser`

,`checkmate`

, and`PreciseSums`

RxODE can only use supported functions (could be breaking); You may add your own functions with

`rxFun`

and their derivatives with`rxD`

RxODE now uses its own internal truncated multivariate normal simulations based on the threefry sitmo library. Therefore random numbers generated within

`RxODE`

like providing`rxSolve(...,omega=)`

will have different results with this new random number generator. This was done to allow internal re-sampling of sigmas/etas with thread-safe random number generators (calling R through`mvnfast`

or R’s simulation engines are not thread safe).`RxODE`

now moved the precise sum/product type options for`sum()`

and`prod()`

to`rxSolve`

or`rxControl`

`cvPost`

now will returned a named list of matrices if the input matrix was named`rxSolve`

will now return an integer`id`

instead of a factor`id`

when`id`

is integer or integerish (as defined by checkmate). Otherwise a factor will be returned.When mixing ODEs and

`linCmt()`

models, the`linCmt()`

compartments are 1 and possibly 2 instead of right after the last internal ODE. This is more aligned with how PK/PD models are typically defined.`EVID=3`

and`EVID=4`

now (possibly) reset time as well. This occurs when the input dataset is sorted before solving.When

`EVID=2`

is present, an`evid`

column is output to distinguish`evid=0`

and`evid=2`

Add the ability to order input parameters with the

`param()`

pseudo-functionAdd the ability to resample covariates with

`resample=TRUE`

or`resample=c("SEX", "CRCL")`

. You can resample all the covariates by`ID`

with`resampleID=TRUE`

or resample the covariates without respect to`ID`

with`resampleID=FALSE`

Comparison of factors/strings is now supported in

`RxODE`

; Therefore ID==“Study-1” is now allowed.Completion for elements of

`rxSolve()`

objects, and`et()`

objects have been added (accessed through`$`

)Completion of

`rxSolve()`

arguments are now included since they are part of the main methodAllow simulation with zero matrices, that provide the simulation without variability. This affects

`rxSolve`

as well as`rxMvnrnd`

and`cvPost`

(which will give a zero matrix whenever one is specified)`et()`

can dose with`length(amt) > 1`

as long as the other arguments can create a event table.Rstudio notebook output makes more sense

Printing upgraded to cli 2.0

- Caching of internal C data setup is now supported increasing speed of
`optim`

code when:- Event Table doesn’t change
- The size of the parameters doesn’t change
`inits`

do not change (though you can specify them as`cmt(0)=...`

in the model and change them by parameters)- See Issue #109

Allow

`while(logical)`

statements with ability to break out if them by`break`

. The while has an escape valve controlled by`maxwhere`

which by default is 10000 iterations. It can be change with`rxSolve(..., maxwhere = NNN)`

Allow accessing different time-varying components of an input dataset for each individual with:

`lag(var, #)`

`lead(var, #)`

`first(var)`

`last(var)`

`diff(var)`

Each of these are similar to the R `lag`

, `lead`

, `first`

, `last`

and `diff`

. However when undefined, it returns `NA`

Allow sticky left-handed side of the equation; This means for an observation the left handed values are saved for the next observations and then reassigned to the last calculated value.

This allows NONMEM-style of calculating parameters like tad:

```
mod1 <-RxODE({
KA=2.94E-01;
CL=1.86E+01;
V2=4.02E+01;
Q=1.05E+01;
V3=2.97E+02;
Kin=1;
Kout=1;
EC50=200;
C2 = centr/V2;
C3 = peri/V3;
d/dt(depot) =-KA*depot;
d/dt(centr) = KA*depot - CL*C2 - Q*C2 + Q*C3;
d/dt(peri) = Q*C2 - Q*C3;
d/dt(eff) = Kin - Kout*(1-C2/(EC50+C2))*eff;
if (!is.na(amt)){
tdose <- time
} else {
tad <- time - tdose
}
})
```

It is still simpler to use:

```
mod1 <-RxODE({
KA=2.94E-01;
CL=1.86E+01;
V2=4.02E+01;
Q=1.05E+01;
V3=2.97E+02;
Kin=1;
Kout=1;
EC50=200;
C2 = centr/V2;
C3 = peri/V3;
d/dt(depot) =-KA*depot;
d/dt(centr) = KA*depot - CL*C2 - Q*C2 + Q*C3;
d/dt(peri) = Q*C2 - Q*C3;
d/dt(eff) = Kin - Kout*(1-C2/(EC50+C2))*eff;
tad <- time - tlast
})
```

If the `lhs`

parameters haven’t been defined yet, they are `NA`

Now the NONMEM-style

`newind`

flag can be used to initialize`lhs`

parameters.Added

`tad()`

,`tad(cmt)`

functions for time since last dose and time since last dose for a compartment; Also added time after first dose and time after first dose for a compartment`tafd()`

,`tafd(cmt)`

; time of last dose`tlast()`

,`tlast(cmt)`

and dose number`dosenum()`

(currently not for each compartment)Changed linear solved systems to use “advan” style

`linCmt()`

solutions, to allow correct solutions of time-varying covariates values with solved systems; As such, the solutions may be slightly different. Infusions to the depot compartment are now supported.- Added sensitivity auto-differentiation of
`linCmt()`

solutions. This allows sensitivities of`linCmt()`

solutions and enables`nlmixr`

focei to support solved systems.- One solution is to use Stan’s auto-differentiation which requires
`C++14`

- One solution is to use Stan’s auto-differentiation which requires
When calculating the empirical Bayesian estimates for with

`rxInner`

(used for nlmixr’s ‘focei’) ignore any variable beginning with`rx_`

and`nlmixr_`

to hide internal variables from table output. This also added`tad=tad()`

and`dosenum=dosenum()`

to the`ebe`

output allowing grouping by id, dose number and use TAD for individual plot stratification.Added ability to prune branching with

`rxPrune`

. This converts`if`

/`else`

or`ifelse`

to single line statements without any`if`

/`then`

branching within them.- Added ability to take more complex conditional expressions, including:
`ifelse(expr, yes, no)`

`x = (x==1)*1 + (!(x==1))*2`

`if (logic){ expr} else if (logic) {expr} else {}`

. The preferred syntax is still only`if`

/`else`

and the corresponding parsed code reflects this preference.- Note
`ifelse`

is not allowed as an ODE compartment or a variable.

- Note

- Switched to
`symengine`

instead of using`sympy`

- Remove dependence on python.
- Since symengine is C-based and doesn’t require the python interface it is much faster than
`sympy`

, though some functions in`sympy`

are no longer accessible. - Also symengine requires R 3.6, so now RxODE requires R 3.6

Added new ODE solving method “indLin”, or inductive linearization. When the full model is a linear ODE system this becomes simply the matrix exponential solution. Currently this requires a different setup.

- Added arbitrary function definition to RxODE using
`rxFun`

- Requires function, arguments and corresponding C-code
- Derivatives (if required) can be added to the derivative table
`rxD`

. When taking deviates without a derivative function, RxODE will use numerical differences.

- Will error if RxODE does not know of a function that you are trying to use; This could be a breaking change. Currently:
- C’s functions from
`math.h`

are supported - R’s function returning and taking doubles are supported
- Other functions can be added using
`rxFun`

and`rxD`

- C’s functions from
Added

`NA`

,`NaN`

,`Inf`

and`+Inf`

handling to a RxODE model. Can be useful to diagnose problems in models and provide alternate solutions. In addition, added R-like functions`is.nan`

,`is.na`

,`is.finite`

and`is.infinite`

which can be called within the RxODE block.- Allowed the following data variables can be accessed (but not assigned or used as a state):
`cmt`

`dvid`

`addl`

`ss`

`amt`

`rate`

`id`

which requires calling the id as factor`ID=="1"`

for instance.

Kept

`evid`

and`ii`

as restricted items since they are not part of the covariate table and are restricted in use.Added the following random number generators; They are thread safe (based on

`threefry`

`sitmo`

and c++11) and your simulations with them will depend on the number of cores used in your simulation (Be careful about reproducibility with large number of threads; Also use parallel-solve type of RxODE simulations to avoid the birthday problem).During ODE solving, the values of these are

`0`

, but while calculating the final output the variable is randomized at least for every output. These are:`rxnorm()`

and`rxnormV()`

(low discrepancy normal)`rxcauchy()`

`rxchisq()`

`rxexp()`

`rxf()`

`rxgamma()`

`rxbeta()`

`rxgeom()`

`rxpois()`

`rxt()`

`rxunif()`

`rxweibull()`

In addition, while initializing the system, the following values are simulated and retained for each individual:

`rinorm()`

and`rinormV()`

(low discrepancy normal)`ricauchy()`

`richisq()`

`riexp()`

`rif()`

`rigamma()`

`ribeta()`

`rigeom()`

`ripois()`

`rit()`

`riunif()`

`riweibull()`

Added

`simeta()`

which simulates a new`eta`

when called based on the possibly truncated normal`omega`

specified by the original simulation. This simulation occurs at the same time as the ODE is initialized or when an ODE is missing, before calculating the final output values. The`omega`

will reflect whatever study is being simulated.Added

`simeps()`

which simulates a new`eps`

from the possibly truncated normal`sigma`

at the same time as calculating the final output values. Before this time, the`sigma`

variables are zero.

All these change the solving to single thread by default to make sure the simulation is reproducible. With high loads/difficult problems the random number generator may be on a different thread and give a different number than another computer/try.

Also please note that the `clang`

and `gcc`

compiler use different methods to create the more complex random numbers. Therefore `MacOS`

random numbers will be different than `Linux`

/`Windows`

at this time (with the exception of uniform numbers).

These numbers are still non-correlated random numbers (based on the sitmo test) with the exception of the vandercorput distributions, so if you increase the number of threads (cores=…) the results should still be valid, though maybe harder to reproduce. The faster the random number generation, the more likely these results will be reproduced across platforms.

Added the ability to integrate standard deviations/errors of omega diagonals and sigma diagonals. This is done by specifying the omega diagonals in the theta matrix and having them represent the variabilities or standard deviations. Then these standard deviations are simulated along with the correlations using the IJK correlation matrix (omega dimension < 10) or a correlation matrix or Inverse Wishart-based correlation matrix (omega dimension > 10). The information about how to simulate this is in the variability simulation vignette.

Now have a method to use

`lotri`

to simulate between occasion variability and other levels of nesting.Added lower gamma functions See Issue #185

Upgraded comparison sort to timsort 2.0.1

- Changed in-place sort to a modified radix sort from
`data.table`

. The radix search was modified to: - Work directly with
`RxODE`

internal solved structures - Assume no infinite values or
`NA`

/`NaN`

values of time - Always sort time in ascending order
Changed sorting to run in a single thread instead of taking over all the threads like data.table

Changed method for setting/getting number of threads based on

`data.table`

’s methodAdded function

`rxDerived`

which will calculate derived parameters for 1, 2, and 3 compartment modelsMore descriptive errors when types of input are different than expected

Moved many C functions to C++. CRAN OpenMP support requires C++ only when C and C++ are mixed. See:

https://stackoverflow.com/questions/54056594/cran-acceptable-way-of-linking-to-openmp-some-c-code-called-from-rcpp

No longer produces C code that create the model variables. Instead, use

`qs`

to serialize, compress and encode in base91 and then write the string into the C file. The`qs`

package then decodes all of that into the model variables. This also increases the compilation speed for models in RxODE.Pre-compile RxODE headers once (if cache is enabled), which increases compilation speed for models in RxODE

`RxODE`

’s translation from the mini-language to C has been refactored

Occasionally RxODE misidentified dual

`lhs`

/`param`

values. An additional check is performed so that this does not happen.For solved matrices with similar names (like “tadd” and “tad”) RxODE will now prefer exact matches instead of the first match found when accessing the items with

`$tad`

.A fix where all ID information is kept with

`keep=c(""..."")`

Transit compartment models using the

`transit`

ODE or variable are now allowed. Also check for more internally parsed items (see Issue #145).Bug fix for

`etSeq`

and`etRep`

where greater than 2 items were mis-calculated

- New plotting engine
- Various bug fixes for upcoming R 4.0 release:
- Dropped some imports for 21 imports restriction
- Fixed incompatibility with new
`ggplot2`

3.3.0 - Fixed allowing
`NA`

s in RxODE dataset - Fixed setting all compartment default values for bioavailability, rate, etc.
- Added additional protection against floating point -> NaN for power functions

- Minor namespace/documentation changes for R 4.0 compatibility

- Added the ability to have an input parameter to be assigned to a new value (Issue #135)
- Added LINPACK authors as contributors
- Added a
`NEWS.md`

file to track changes to the package