% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/MFItoRAU.R
\name{.convert_mfi_to_dilution_no_bounds}
\alias{.convert_mfi_to_dilution_no_bounds}
\title{Convert mfi to dilution using known standard curve fit and no bounds}
\usage{
.convert_mfi_to_dilution_no_bounds(mfi, params, min_relative_dilution)
}
\arguments{
\item{mfi}{Known mfi of samples}

\item{params}{Known parameters for five parameter logistic fit.}

\item{min_relative_dilution}{Known minimum value of dilution in the standard curve. Relative means setting S1 to a dilution/RAU/concentration of 1.}
}
\value{
Returns the dilution of each sample in mfi.
}
\description{
Convert mfi to dilution using known standard curve fit and no bounds unless you are below the asymptote of the standard curve.
In this situation we set your value to min_relative_dilution. I dunno argue?
}
\examples{
# This function is generally called inside higher-level analysis workflows.
# Below is a minimal self-contained example using dummy values.

# Dummy five-parameter logistic fit parameters:
# a, b, c, d, e  (with e typically supplied on the log scale)
dummy_params <- c(a = 10000, b = 1.2, c = 0.05, d = 50, e = log(0.01))

# Example MFI value
mfi_example <- 1500

# Minimum relative dilution from the standard curve
min_rel_dil <- 1

# Convert MFI to dilution without bounds
.convert_mfi_to_dilution_no_bounds(mfi_example, dummy_params, min_rel_dil)
}
\author{
Eamon Conway
}
