monoexp_start: Grid-profiled starting estimates for the monoexponential...

In mnirs: Muscle Near-Infrared Spectroscopy Processing and Analysis

Grid-profiled starting estimates for the monoexponential model

Description

Vector-level initialiser behind monoexp_init(), called directly by the kinetics worker on the fit window. Profiles tau (and TD for the 4-parameter model) on a coarse grid and keeps the RSS-minimising start (cf. biexp_start()). The model is linear in A and B once tau and TD are held, so the asymptotes are solved by least squares at every grid point at once. Point estimates from derivative changepoints or log-linearisation are too sensitive to noise, overshoot, and plateau data on real NIRS signals, and can strand nls with a singular gradient.

Usage

monoexp_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.