| nlsrSS {nlsr} | R Documentation |
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 |
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