| models_lnln {bioset} | R Documentation |
Use these functions to transform x and y using the natural logarithm and calculate a linear model, plot the model and use it to calculate x-values from the model data and y-values (inverse function).
Those function are intended to be used in set_calc_concentrations /
sets_read to be applied to the calibrators (fit_lnln) and interpolate
concentrations from the raw values (interpolate_lnln). Use plot_lnln
to visually inspect goodness of fit.
fit_lnln: Apply ln to x and y and calculate a linear model from x and y.
plot_lnln: Draw the plot for the model that can be calculated with
fit_lnln. Uses ggplot2::ggplot if available.
interpolate_lnln: Inverse fit_lnln using model and calculate x
values from y values.
fit_lnln(x, y) plot_lnln(x, y) interpolate_lnln(y, model)
x |
The x coordinates of the points. |
y |
The y coordinates of the points. |
model |
The line model. |
fit_lnln: The model.
plot_lnln: The plot.
interpolate_lnln: The calculated x values.
set_calc_concentrations, sets_read, models_linear
# generate data x <- c(2.718282, 20.085537, 54.598150, 1096.633158) # x is known for these values y_known <- c(33.11545, 665.14163, 2980.95799, 268337.28652) # we will calculate x for those: y_unknown <- c(148.4132, 13359.7268, 59874.1417) model <- fit_lnln(x = x, y = y_known) model plot_lnln(x = x, y = y_known) interpolate_lnln(y = y_unknown, model) rm(x, y_known, y_unknown, model)