expdrift_start: Grid-profiled starting estimates for the exponential-drift...

In mnirs: Muscle Near-Infrared Spectroscopy Processing and Analysis

Grid-profiled starting estimates for the exponential-drift model

Description

Vector-level initialiser behind expdrift_init(), called directly by the kinetics worker on the fit window. Profiles tau (and TD) on a coarse grid and keeps the RSS-minimising start (cf. monoexp_start()). The model is linear in A, B, and slope_B once tau and TD are held, so those are solved by least squares at every grid point at once via solve_grid3(). User-fixed tau, TD, and drift_fraction narrow the grids; the linear parameters are always solved free, as this is only a seed. tau is capped so the drift onset stays inside the record; a grid point whose hinge has no support is singular and skipped.

Usage

expdrift_start(x, t, fixed = list(), has_TD = FALSE)

Arguments

x, t	Numeric vectors of the response and time.
fixed	A named list of user-fixed parameter values, which narrow the grids and constrain the free estimates.
has_TD	Logical; include the time delay TD.

Value

A named numeric vector of starting estimates in model order.

mnirs documentation built on Sept. 13, 2026, 1:06 a.m.