SSlogistic: Self-starting logistic model

In mnirs: Muscle Near-Infrared Spectroscopy Processing and Analysis

Self-starting logistic model

Description

Creates initial coefficient estimates for a selfStart wrapper around logistic(), for use with stats::nls(). Supports both the 4-parameter symmetric (A, B, xmid, slope) and 5-parameter asymmetric (A, B, xmid, slope, asym) forms; arity is inferred from the formula passed to stats::nls().

Usage

SSlogistic(t, A, B, xmid, slope, asym)

Arguments

t	A numeric vector of the predictor variable (time).
A	A numeric parameter for the starting asymptote of the response variable.
B	A numeric parameter for the ending asymptote of the response variable.
xmid	A numeric parameter for the time at the inflection point (the steepest point) of the curve, in units of the predictor variable t.
slope	A numeric parameter for the response rate dx/dt at the inflection xmid.
asym	A numeric parameter for the asymmetry index of the curve; the fraction of the amplitude (y(xmid) - A) / (B - A) at which the inflection xmid occurs, in ⁠(0, 1)⁠. asym = 0.5 is symmetric and equivalent to the 4-parameter form. If NULL (default), a symmetric 4-parameter model is used.

Details

Model formulas

• 4-parameter: x ~ SSlogistic(t, A, B, xmid, slope)

• 5-parameter: x ~ SSlogistic(t, A, B, xmid, slope, asym)

The 4-parameter form is used by analyse_kinetics() with method = "sigmoidal" and shape = "symmetric". The 5-parameter asymmetric form is retained for advanced/experimental use only; analyse_kinetics() instead dispatches to SSgompertz() / SSgompertz_left() for asymmetric shapes, which are more stable. stats::nls() reads the free parameters from the formula right-hand side, so omitting asym incurs no degrees-of-freedom penalty.

Fixing parameters

Any parameter may be held constant by writing a value in place of its name in the formula, e.g. x ~ SSlogistic(t, A = 0, B, xmid, slope) fixes the starting asymptote at A = 0. Fixed parameters are excluded from estimation and are not returned by stats::coef().

Value

A numeric vector of predicted values the same length as the predictor variable t.

See Also

logistic(), analyse_kinetics(), stats::nls(), stats::selfStart(), stats::SSfpl(), SSgompertz()

Examples

## create an asymmetric logistic curve with random noise
set.seed(15)
t <- 1:60
x <- logistic(t, A = 10, B = 100, xmid = 30, slope = 4, asym = 0.3) +
    rnorm(length(t), 0, 2)
data <- data.frame(t, x)

## 4-parameter fit
model4 <- nls(x ~ SSlogistic(t, A, B, xmid, slope), data = data)
summary(model4)

## 5-parameter fit on the same data
model5 <- nls(x ~ SSlogistic(t, A, B, xmid, slope, asym), data = data)
summary(model5)

## fix the starting asymptote `A` at a known value
model_fixed <- nls(x ~ SSlogistic(t, A = 10, B, xmid, slope), data = data)
summary(model_fixed)

y4 <- predict(model4, data)
y5 <- predict(model5, data)


    if (requireNamespace("ggplot2", quietly = TRUE)) {
        ggplot2::ggplot(data, ggplot2::aes(t, x)) +
            theme_mnirs() +
            ggplot2::geom_point() +
            ggplot2::geom_line(ggplot2::aes(y = y5, colour = "5-param")) +
            ggplot2::geom_line(ggplot2::aes(y = y4, colour = "4-param"))
    }

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