Normalize Samples

Calculate sample concentration based on the fit of standard dilutions.

Usage

normalizeSmp(
  smp,
  smpvar,
  resvar,
  dilvar,
  FUNinv,
  par,
  bounds,
  fitflag,
  fitlog,
  trim.flat = TRUE,
  extrapolate.low = FALSE,
  extrapolate.up = FALSE
)

Arguments

smp

data frame containing samples

smpvar

character string indicating sample variable.

dilvar, resvar

character strings for dilution variable and results.

FUNinv

inverse function to infer sample concentration

par

values of model function parameters

bounds

named vector with values for extrema and bounds indicating "flat" regions of the curve

fitflag

flag for the fit as returned by fitStd

fitlog

character string indicating if standard values should be log-transformed for fitting. If the string contains _x_, xvar will be transformed, if it contains _y_ - yvar.

trim.flat

logical value determining how the values of yvar are trimmed. If TRUE, they will be trimmed at the bounds where the curve starts to flatten out (automatically determined as maxima of the third derivative of the function). If FALSE, yvar will be trimmed at extrema, defined as the range of standards or asymptotes of the fit (whichever are less extreme).

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.

Value

A data frame.

Details

coming up