Use a Standard Curve to Calculate Unknown Values

std_curve_calc(std_curve, unknowns, digits = 3)

Arguments

std_curve: A linear model, created with either lm() or standard::std_curve_fit()
unknowns: A numeric vector of unknown values, which the standard curve will be used to predict their values.
digits: Number of decimal places for calculations.

Value

a tibble with a column for the unknown values, and a column .fitted for the predicted values, based on the standard curve.

Examples

library(standard)

# Protein concentrations of the standards used in the assay
prot <- c(
  0.000, 0.016, 0.031, 0.063, 0.125, 0.250, 0.500, 1.000,
  0.000, 0.016, 0.031, 0.063, 0.125, 0.250, 0.500, 1.000
)

# absorbance readins from the standards used in the assay
abs <- c(
  0.329, 0.352, 0.349, 0.379, 0.417, 0.491, 0.668, 0.956,
  0.327, 0.341, 0.355, 0.383, 0.417, 0.446, 0.655, 0.905
)
assay_data <- data.frame(
  Protein = prot,
  Absorbance = abs
)

# unknown concentrations
unk <- c(0.554, 0.568, 0.705)


assay_data |>
  std_curve_fit(Protein, Absorbance) |>
  std_curve_calc(unk) |>
  plot()