nlmixr 2.0.1

User interface changes

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)

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.
- Uses RxODE/stan's math headers to calculate the sensitivities of the super-positioned linCmt() solutions.
- This uses the 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)*err
- combined2: trans(y) = trans(f) + sqrt(a^2+b^2*f^(2c))*err
focei 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)*err
- combined2: trans(y) = trans(f) + sqrt(a^2+b^2*f^(2c))*err
saem 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
Added the low-discrepancy "vandercorput" normal sequence from SITMO/RxODE; In theory this will cover the domain quickly and evenly possibly allowing a better solution. This can be called with saemControl(normal="vandercorput").
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)*err
- combined2: y = f + sqrt(a^2+b^2*f^2)*err
- See nlmixrdevelopment#428
- Thanks to Johannes Ranke (@jranke) for the nlme patch and the catch
Can switch with nlmeControl(addProp="combined1") to use the combined1 type of error model

bootstrapFit now calculates the bootstrap confidence bands and (optionally) will compare with the theoretical chi-squared distribution to help assess their adequacy.

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

Aligned saem and focei additive + proportional error models, so saem additive+proportional outputs will be different using the correct focei method

Note this includes all the RxODE changes including dropping python.