focei subject initialization, see #566Fix for nlmixrSim CMT to have a factor that matches the RxODE definition (issue #501)
Give instructions on how to reinstall nlmixr if it is linked to a different version of RxODE. (#555)
Now inform which parameters are near the boundary (#544)
The saem estimation routine will now increase the tolerance when ODE solving is difficult; This can be controlled with odeRecalcFactors and maxOdeRecalc. This is similar to the handling that focei already uses.
For focei family estimation methods:
If the inner problem couldn’t solve the ODE using the forward sensitivities, try using numerical differences to approximate the derivatives needed for the focei problem. A warning will be issued when this occurs. This requires RxODE 1.1.0 that always generates the finite difference prediction model. If RxODE is an earlier version, only apply this when the finite differences are supplied to nlmixr. This occurs when there are ETAs on the dose based events like duration, lag time, bioavaibility etc.
If eta nudge is non-zero, when resetting an ETA estimate, try the zero estimate first, and then the nudged locations.
When there is an ODE system for an individual that cannot be optimized in the inner problem, adjust that individual’s objective function by 100 points. This can be controlled by foceiControl(badSolveObjfAdj=100)
Theta reset now will now make sure the parameter is estimated and between the proper bounds before resetting.
$simInfo non longer tries to generate the covariance step, and will simply have a $simInfo$thetaMat entry of NULL if the covariance step was unsuccessful.
With vpc() if the cmt conversion isn’t working correctly, fall back to compartment numbers.
Take out symbol stripping based on CRAN policies
Fall back gracefully when rbind doesn’t work in parameter histories.
Correctly print out the number of compartments based on the new RxODE linCmt() that was updated to support solved systems in focei. (Reported by Bill Denney #537).
Use strict headers since Rcpp now is moving toward strict headers. Also changed all the Calloc to R_Calloc, Free to R_Free, and DOUBLE_EPS to DBL_EPSILON.
gnlmm no longer imports the data.frame to an RxODE event table. This should speed up the routine slightly and (more importantly) make it easier to specify time varying covariates.
Now can use the following for combinde error models: foceiControl(addProp=1) foceiControl(addProp=2) saemControl(addProp=1) saemControl(addProp=2)
Bug-fix for SAEM add+prop and other error models that are optimized with nelder mead simplex (#503)
Bug-fix for more complex SAEM models that were not parsing and running. (Issue #502, #501)
Issue the “NaN in prediction” once per SAEM problem (#500)
Detection of initial conditions was rewritten to enable additional features in the initial conditions (#322). The most important user-facing change is that now arbitrary R expressions can be used when setting initial conditions such as tvCL <- log(c(2,3,4)) (#253) instead of simply tvCL <- log(3)
The function as.nlmixrBounds() now supports adding the columns that are missing into the input data.frame.
omega definitions can be correlation matrices (#338)
Can specify keep= and drop= in the nlmixr function to keep and drop columns in nlmixr output. Can also specify control=list(keep=,drop=) or nlmixr(...,keep=,drop=) to keep/drop columns (#260)
focei changes:Uses RxODE to re-arrange the problem so it does not include if/else in the model (ie. un-branched code). This allows sensitivities to be calculated in one pass saving time for multiple endpoint models and models with if/else in them.
linCmt() now uses solved systems instead of translating to ODEs.
RxODE/stan’s math headers to calculate the sensitivities of the super-positioned linCmt() solutions.advan solutions and hence supports support time-varying covariates.focei now supports censoring in the same way monolix does, with cens and limit columns
focei now allows etas on dose-related modeled events like alag, f, etc by finite difference sensitivities.
focei now supports 2 combined additive + proportional error models;
combined1: trans(y) = trans(f) + (a+b*f^c)*errcombined2: trans(y) = trans(f) + sqrt(a^2+b^2*f^(2c))*errfocei etaNudge parameters were changed to use quadrature points covering 95% percent of a standard normal.
With zero gradients, Gill differences are recomputed to try to find a non-zero gradient.
Now when running if a zero gradient is detected, reset the problem (theta reset) and re-estimated with outerOpt="bobyqa"
Now when running a model where the last objective function is not the minimum objective function, issue a warning and skip the covariance step. (See Issue #403)
focei proportional and power models are more tolerant of 0 predictions in your data
saem fits now gracefully fall back to the focei likelihood when they support files are no longer on the loaded disk
saem phi pile is now saved in the RxODE::rxTempDir() which can be customized to allow the phi file to remain after R has exited
saem fits now can add in fo, foce and focei likelihood
saem fits now use liblsoda by default and are multi-threaded when running (controlled by RxODE)
saem now supports time-varying covariates (like clock-time)
saem now supports 2 combined additive + proportional error models:
combined1: trans(y) = trans(f) + (a+b*f^c)*errcombined2: trans(y) = trans(f) + sqrt(a^2+b^2*f^(2c))*errsaem proportional and power models are more tolerant of 0 predictions in your data
saem now supports censoring a similar way as monolix does, with cens and limit columns
The default of saem additive + proportional error has been switched to combined2, which was the focei default, but you can change this back with saemControl(addProp="combined2"). The table results will likely be different because in the last release the saem calculated combined1 and then used these coefficients in the combined2 focei problem.
nlme will now support 2 combined additive + proportional error models (if the patched version of nlme is used)
combined1: y = f + (a+b*f)*errcombined2: y = f + sqrt(a^2+b^2*f^2)*errnlmeControl(addProp="combined1") to use the combined1 type of error modelbootstrapFit now calculates the bootstrap confidence bands and (optionally) will compare with the theoretical chi-squared distribution to help assess their adequacy.
covarSearchAuto now allows automatic forward/backward covariate selection
Added auto-completion of nlmixr object properties accessed by $. This works for major editors including Rstudio, ESS, and Base R itself.
Changed the way that Rstudio notebooks display nlmixr objects; It should be more legible in Rstudio.
Graphics have been revamped to show censoring (including adding ggplot stat/geom geom_cens) as well as use RxODE’s ggplot theme (rxTheme()). Additionally time after dose is calculated as tad for all nlmixr models
Tables generation has been refactored; npde uses the arma and RxODE random number generators which may change results. Also the default of ties=TRUE has been changed to ties=FALSE. npde calculations have been threaded with OpenMP to speed up the calculation as well. This refactoring was required to have the dv imputation between cwres and npde use the same method. The npde option now calculates the decorrelated npd as well, (which is the recommended weighted residual; see Nguyen 2017)
saem and focei additive + proportional error models, so saem additive+proportional outputs will be different using the correct focei methodNote this includes all the RxODE changes including dropping python.