normalizeSmp: Normalize Samples
In EPPIcenter/flexfit: Flexible Format Standard Curve Fitting and Data Processing

View source: R/normalizeSmp.R

normalizeSmp

R Documentation

Normalize Samples

Description

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.