parametric.nlsfit.cov: parametric.nlsfit.cov

In hadron: Analysis Framework for Monte Carlo Simulation Data in Physics

parametric.nlsfit.cov

Description

NLS fit with parametric bootstrap and covariance

Usage

parametric.nlsfit.cov(fn, par.guess, boot.R, y, x, cov, lower = rep(x = -Inf,
  times = length(par.guess)), upper = rep(x = +Inf, times =
  length(par.guess)), ..., bootstrap = TRUE, na.rm = FALSE)

Arguments

fn	fn(par, x, ...). The (non-linear) function to be fitted to the data. Its first argument must be the fit parameters named par. The second must be x, the explaining variable. Additional parameters might be passed to the function. Currently we pass boot.r which is 0 for the original data and the ID (1, ...) of the bootstrap sample otherwise. As more parameters might be added in the future it is recommended that the fit function accepts ... as the last parameter to be forward compatible.
par.guess	initial guess values for the fit parameters.
boot.R	numeric. Number of bootstrap samples to generate.
y	the data as a one-dimensional numerical vector to be described by the fit function.
x	values of the explaining variable in form of a one-dimensional numerical vector.
cov	numeric matrix, square, length of x or missing. Covariance between the various variables in the vector x.
lower	Numeric vector of length length(par.guess) of lower bounds on the fit parameters. If missing, -Inf will be set for all.
upper	Numeric vector of length length(par.guess) of upper bounds on the fit parameters. If missing, +Inf will be set for all.
...	Additional parameters passed to fn, gr and dfn.
bootstrap	boolean. If TRUE, bootstrap is used.
na.rm	logical. If set to true, NAs in y and dy will be ignored. If x-errors are taken into account, NAs in x and dx will be ignored, too.

Value

See simple.nlsfit.

See Also

Other NLS fit functions: bootstrap.nlsfit(), parametric.bootstrap.cov(), parametric.bootstrap(), parametric.nlsfit(), plot.bootstrapfit(), predict.bootstrapfit(), print.bootstrapfit(), simple.nlsfit(), summary.bootstrapfit()

hadron documentation built on Sept. 9, 2022, 5:06 p.m.