add_curve_fit: Add curve fit

In tidyplots: Tidy Plots for Scientific Papers

Add curve fit

Description

Add curve fit

Usage

add_curve_fit(
  plot,
  dodge_width = NULL,
  method = "loess",
  linewidth = 0.25,
  alpha = 0.4,
  preserve = "total",
  ...
)

Arguments

plot	A tidyplot generated with the function tidyplot().
dodge_width	For adjusting the distance between grouped objects. Defaults to 0.8 for plots with at least one discrete axis and 0 for plots with two continuous axes.
method	Smoothing method (function) to use, accepts either NULL or a character vector, e.g. "lm", "glm", "gam", "loess" or a function, e.g. MASS::rlm or mgcv::gam, stats::lm, or stats::loess. "auto" is also accepted for backwards compatibility. It is equivalent to NULL. For method = NULL the smoothing method is chosen based on the size of the largest group (across all panels). stats::loess() is used for less than 1,000 observations; otherwise mgcv::gam() is used with formula = y ~ s(x, bs = "cs") with method = "REML". Somewhat anecdotally, loess gives a better appearance, but is O(N^{2}) in memory, so does not work for larger datasets. If you have fewer than 1,000 observations but want to use the same gam() model that method = NULL would use, then set ⁠method = "gam", formula = y ~ s(x, bs = "cs")⁠.
linewidth	Thickness of the line in points (pt). Typical values range between 0.25 and 1.
alpha	A number between 0 and 1 for the opacity of an object. A value of 0 is completely transparent, 1 is completely opaque.
preserve	Should dodging preserve the "total" width of all elements at a position, or the width of a "single" element?
...	Arguments passed on to ggplot2::geom_smooth().

Value

A tidyplot object.

Examples

time_course |>
  tidyplot(x = day, y = score, color = treatment) |>
  add_curve_fit()

# Changing arguments
time_course |>
  tidyplot(x = day, y = score, color = treatment) |>
  add_curve_fit(linewidth = 1)

time_course |>
  tidyplot(x = day, y = score, color = treatment) |>
  add_curve_fit(alpha = 0.8)

# Remove confidence interval
time_course |>
  tidyplot(x = day, y = score, color = treatment) |>
  add_curve_fit(se = FALSE)

tidyplots documentation built on April 3, 2025, 9:33 p.m.