nlsrSS: nlsrSS - solve selfStart nonlinear least squares with nlsr...

In nlsr: Functions for Nonlinear Least Squares Solutions - Updated 2022

nlsrSS - solve selfStart nonlinear least squares with nlsr package

Description

This function uses the getInitial() function to estimate starting parameters for a Gauss-Newton iteration, then calls nlsr::nlxb() appropriately to find a solution to the required nonlinear least squares problem.

Usage

nlsrSS(formula, data)

Arguments

formula	a model formula incorporating a selfStart function in the right hand side
data	a data frame with named columns that allow evaluation of the formula

Value

A solution object of class nlsr.

List of solution elements

resid	weighted residuals at the proposed solution
jacobian	Jacobian matrix at the proposed solution
feval	residual function evaluations used to reach solution from starting parameters
jeval	Jacobian function (or approximation) evaluations used
coefficients	a named vector of proposed solution parameters
ssquares	weighted sum of squared residuals (often the deviance)
lower	lower bounds on parameters
upper	upper bounds on parameters
maskidx	vector if indices of fixed (masked) parameters
weights	specified weights on observations
formula	the modeling formula
resfn	the residual function (unweighted) based on the formula

Author(s)

J C Nash 2022-9-14 nashjc _at_ uottawa.ca

nlsr documentation built on Sept. 8, 2023, 5:48 p.m.