Linear model plot type

Description

Type function for plotting a linear model fit. Arguments are passed to lm.

Usage

type_lm(se = TRUE, level = 0.95, weights = NULL)

Arguments

se	logical. If TRUE, confidence intervals are drawn.
level	the confidence level required.
weights	an optional numeric vector of observation weights for the model fit, of the same length as the number of data points. Weights can also be supplied via the top-level weights argument of tinyplot (which is evaluated with non-standard evaluation in the formula method, and takes precedence if both are given).

Examples

library("tinyplot")

# "lm" type convenience string
tinyplot(Sepal.Width ~ Petal.Width, data = iris, type = "lm")

# Grouped model fits (here: illustrating an example of Simpson's paradox)
tinyplot(Sepal.Width ~ Petal.Width | Species, data = iris, type = "lm")
tinyplot_add(type = "p")

# Use `type_lm()` to pass extra arguments for customization
tinyplot(Sepal.Width ~ Petal.Width, data = iris, type = type_lm(level = 0.8))

# Weighted fit example, either as a top-level argument (which supports
# non-standard evaluation in the formula method)...
s77 = as.data.frame(state.x77)
tinyplot(`Life Exp` ~ Income, data = s77, type = "lm", weights = Population)

# ...or directly via the type constructor (requires an evaluated vector)
tinyplot(`Life Exp` ~ Income, data = s77, type = type_lm(
  weights = s77$Population))