dot-rxAdjointGradEvalC: Evaluate a prebuilt adjoint objective gradient in C++

In rxode2: Facilities for Simulating from ODE-Based Models

Evaluate a prebuilt adjoint objective gradient in C++

Description

Covers continuous ODE, modeled bioavailability (F), modeled lag (alag), replace/multiply events, and modeled-rate/duration infusions. A single forward solve emits the Jacobian, forcing and dose-dual quantities on a fine grid; the backward costate + quadrature sweep, event jumps and gradient accumulation run in C++ (rxode2AdjointSweep). Numerically equivalent to .rxAdjointGradEval().

Usage

.rxAdjointGradEvalC(
  build,
  params,
  obsTimes,
  obs,
  weight = 1,
  denseBy = 0.01,
  atol = 1e-10,
  rtol = 1e-10
)

Arguments

build	object returned by .rxAdjointGradBuild().
params	named numeric vector of parameter values.
obsTimes	numeric observation times.
obs	numeric observed values aligned with obsTimes.
weight	numeric scalar or vector of least-squares observation weights (ignored when errModel is supplied).
denseBy	grid spacing for the forward checkpoint trajectory; smaller values reduce the covariate-interpolation error.
atol, rtol	solver tolerances used for both the forward checkpoint and the backward sweeps.

Value

named numeric vector dG/dtheta over the build's calcSens.

Author(s)

Matthew L. Fidler

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