fitStd: Fit Standards
In EPPIcenter/flexfit: Flexible Format Standard Curve Fitting and Data Processing

View source: R/fitStd.R

fitStd

R Documentation

Fit Standards

Description

Fit a specified function to standards (serial dilutions). Optionally an interactive procedure that allows to remove outliers, evaluate resulting fits, perform revisions, and record a message regarding the fit.

Usage

fitStd(
  std,
  xvar,
  yvar,
  model = "sigmoid",
  Alow = NULL,
  asym = TRUE,
  interactive = TRUE,
  monot.prompt = FALSE,
  rm.before = FALSE,
  rm.after = interactive,
  maxrm = 2,
  set.bounds = FALSE,
  overwrite.bounds = FALSE,
  bg = NULL,
  vsmp = NULL,
  optmethod = "Nelder-Mead",
  maxit = 5000,
  extrapolate.low = FALSE,
  extrapolate.up = FALSE,
  info = "",
  ifix = NULL,
  tcklab = NULL,
  stdcol = c("firebrick3", "darkslategray"),
  rugcol = c("cadetblue", "purple", "firebrick2"),
  ...
)

Arguments

`std`	matrix or data frame with standards for fitting.
`xvar, yvar`	character strings for the variables used to fit a standard curve. If `NULL`, first two columns are assumed to be `x` and `y` variables.
`model`	the model to be fit.
`Alow`	lower asymptote for the sigmoid model. If `NULL`, the lower asymptote will be estimated, adding an extra parameter to the model. To fix the asymptote at the level of background, specify `"bg"`. Numeric value of `Alow` will force the asymptote to be fixed at the provided level.
`asym`	if `TRUE`, asymmetry in the fit is allowed, adding an extra parameter to the model.
`interactive`	logical value. If `TRUE`, the user is prompted to evaluate the standards (and/or the fit) and asked to remove outliers if needed. `TRUE` value takes precedence over `rm.before` and `rm.after`: if both are `FALSE`, `rm.after` is reset to `TRUE`.
`monot.prompt`	if `TRUE`, the user is prompted to evaluate the standards and possibly remove outliers if the standards are not monotonic (increasing). `FALSE` value is ignored if `interactive` is `TRUE`.
`rm.before`	logical value indicating if potential outliers should be removed before the model is fitted. Ignored if `interactive` is `FALSE`.
`rm.after`	logical value indicating if potential outliers should be removed after the model is fitted. Ignored if `interactive` is `FALSE`.
`maxrm`	maximum number of outliers to remove.
`set.bounds`	if `TRUE`, the user is given the option to manually set the bound that is not set automatically. In that case, the prompt appears even if `interactive` is `FALSE`.
`overwrite.bounds`	logical value indicating the option to overwrite automatically set bounds. Ignored if `interactive` is `FALSE`.
`bg`	values for background spots.
`vsmp`	sample values.
`optmethod`	method to be used in optimization.
`maxit`	maximum number of iterations in optimization.
`extrapolate.low`	if `TRUE`, sample values beyond lower bounds will be processed by extrapolation of the standard curve (not recommended). Takes precedence over `trim.flat` value.
`extrapolate.up`	if `TRUE`, sample values beyond upper bounds will be processed by extrapolation of the standard curve (not recommended). Takes precedence over `trim.flat` value.
`info`	information about a particular run for warning messages.
`ifix`	sorted integer vector of length 3 with indices of standards to be used for getting starting values for optimization.
`tcklab`	tick labels for x-axis.
`stdcol`	vector of two colors for the standard points and the fit on the plot.
`rugcol`	vector of three colors for the rugplot, which indicates sample values (inside the bounds, between the bounds and extrema, and beyond extrema).
`...`	further graphical parameters.