Fit Standards — fitStd • flexfit

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.

Value

A list containing parameters of the fit and bounds of the fit (named vectors), as well as indices of removed points (if any) and flags r.

Details

to be added