v2.0.3

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)

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.

  • 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 changes

• 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

• 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 changes

• 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 #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

New Utilities

• bootstrapFit 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

General Changes

• 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)

Bug Fixes

• 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.