R: Linear model functions.

models_linear {bioset} | R Documentation

## Linear model functions.

### Description

Use these functions to calculate a linear model from data, 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_linear`) and interpolate concentrations from the raw values (`interpolate_linear`). Use `plot_linear` to visually inspect goodness of fit.

- `fit_linear`: Calculate a linear model from x and y.

- `plot_linear`: Draw the plot for the model that can be calculated with `fit_linear`. Uses ggplot2::ggplot if available.

- `interpolate_linear`: Inverse `fit_linear` using `model` and calculate x values from y values.

### Usage

    fit_linear(x, y)

    plot_linear(x, y)

    interpolate_linear(y, model)

### Arguments

`x` | The x coordinates of the points.
`y` | The y coordinates of the points.
`model` | The line model.

### Value

- `fit_linear`: The line model.

- `plot_linear`: The plot.

- `interpolate_linear`: The calculated x values.

### See Also

set_calc_concentrations, sets_read, models_lnln

### Examples

    # generate data
    x <- c(1, 3, 4, 7)
    y_known <- c(3.5, 6.5, 8, 12.5)  # x is known for these values
    y_unknown <- c(5, 9.5, 11)       # we will calculate x for those

    model <- fit_linear(x = x, y = y_known)
    model

    plot_linear(x = x, y = y_known)

    interpolate_linear(y = y_unknown, model)

    rm(x, y_known, y_unknown, model)

[Package bioset version 0.2.2 Index]