rxSolveAdjoint: Solve a model with adjoint (backward) sensitivities, drop-in...

In rxode2: Facilities for Simulating from ODE-Based Models

Solve a model with adjoint (backward) sensitivities, drop-in for forward sens

Description

Solves object as rxSolve() would, then appends ⁠rx__sens_<state>_BY_<param>__⁠ columns computed via adjoint (backward) sensitivity analysis. Same column names and output structure as rxSolve(object, ..., calcSens=). Prefer .rxAdjointGrad() when only a scalar objective gradient is needed.

Usage

rxSolveAdjoint(
  object,
  params,
  events,
  calcSens,
  adjStates = NULL,
  denseBy = 0.01,
  atol = 1e-08,
  rtol = 1e-06,
  ...
)

Arguments

object	model definition accepted by rxode2().
params	named numeric vector of parameter values.
events	event table / data used to define dosing and sampling times; sampling (evid==0) times become the sensitivity output times.
calcSens	character vector of parameter names to differentiate with respect to.
adjStates	character vector of output states of interest; defaults to all ODE states (full forward-sensitivity parity).
denseBy, atol, rtol	passed to the adjoint checkpoint solve; see .rxAdjointSolveEvalC().
...	additional arguments passed to the primal rxSolve() call.

Value

the standard rxSolve() output (as returnType="data.frame") with ⁠rx__sens_<state>_BY_<param>__⁠ columns appended.

Author(s)

Matthew L. Fidler

rxode2 documentation built on July 28, 2026, 5:08 p.m.