kappa4NLSobj: Sigmoidal curve fitting.

In mtloots/alR: Arc Lengths of Statistical Functions

Description

Support functions for fitting four-parameter kappa sigmoidal curves.

Usage

kappa4NLSobj(parms, xvec, y, x_min, x_max)

kappa4NLScon(parms, xvec, y, x_min, x_max)

kappa4NLShin(parms, xvec, y, x_min, x_max)

kappa4NLSheq(parms, xvec, y, x_min, x_max)

kappa4ALobj(parms, al_samp, x_min, x_max, q1, q2)

kappa4ALcon(parms, al_samp, x_min, x_max, q1, q2)

kappa4ALhin(parms, al_samp, x_min, x_max, q1, q2)

kappa4ALheq(parms, al_samp, x_min, x_max, q1, q2)

Arguments

parms	A numeric vector of parameters to be estimated.
xvec	A numeric vector of independent observations.
y	A numeric vector of dependent observations.
x_min	The minimum xvec value.
x_max	The maximum xvec value.
al_samp	The sample arc length statistic.
q1, q2	Numeric vectors, for the lower and upper bounds of the intervals over which arc lengths are to be computed.

Value

kappa4NLSobj: The nonlinear least squares objective function.

kappa4NLScon: A vector with three conditions evaluated.

kappa4NLShin: A vector specifying a single nonlinear inequality constraint.

kappa4NLSheq: A vector specifying two nonlinear equality constraints.

kappa4ALobj: The arc length objective function.

kappa4ALcon: A vector with three conditions evaluated.

kappa4ALhin: A vector specifying a single nonlinear inequality constraint.

kappa4ALheq: A vector specifying two nonlinear equality constraints.

mtloots/alR documentation built on May 23, 2019, 8:18 a.m.