plot_qq: Create a quantile-quantile plot

In tscv: Functions and Utilities for Tidy Time Series Forecasting and Time Series Cross-Validation

Create a quantile-quantile plot

Description

Create a quantile-quantile plot for one or more numeric variables.

Usage

plot_qq(
  data,
  x,
  facet_var = NULL,
  facet_scale = "free",
  facet_nrow = NULL,
  facet_ncol = NULL,
  color = NULL,
  title = NULL,
  subtitle = NULL,
  xlab = NULL,
  ylab = NULL,
  caption = NULL,
  point_size = 2,
  point_shape = 16,
  point_color = "grey35",
  point_fill = "grey35",
  point_alpha = 0.25,
  line_width = 0.25,
  line_type = "solid",
  line_color = "grey35",
  line_alpha = 1,
  band_color = "grey35",
  band_alpha = 0.25,
  theme_set = theme_tscv(),
  theme_config = list(),
  ...
)

Arguments

data	A data.frame, tibble, or tsibble in long format.
x	Unquoted column in data containing numeric values.
facet_var	Optional unquoted column in data used for faceting.
facet_scale	Character value defining facet axis scaling. Common values are "free", "fixed", "free_x", and "free_y".
facet_nrow	Optional integer. Number of rows in the facet layout.
facet_ncol	Optional integer. Number of columns in the facet layout.
color	Optional unquoted column in data used to map point, line, and confidence-band colors.
title	Character value. Plot title.
subtitle	Character value. Plot subtitle.
xlab	Character value. Label for the x-axis.
ylab	Character value. Label for the y-axis.
caption	Character value. Plot caption.
point_size	Numeric value defining the point size.
point_shape	Numeric or character value defining the point shape.
point_color	Character value defining the point outline color. Ignored when color is supplied.
point_fill	Character value defining the point fill color. Ignored when color is supplied.
point_alpha	Numeric value between 0 and 1 defining point transparency.
line_width	Numeric value defining the qq-line width.
line_type	Character or numeric value defining the qq-line type.
line_color	Character value defining the qq-line color. Ignored when color is supplied.
line_alpha	Numeric value between 0 and 1 defining line transparency.
band_color	Character value defining the confidence-band fill color. Ignored when color is supplied.
band_alpha	Numeric value between 0 and 1 defining confidence-band transparency.
theme_set	A complete ggplot2 theme.
theme_config	A named list with additional arguments passed to ggplot2::theme().
...	Further arguments passed to qqplotr::stat_qq_point(), qqplotr::stat_qq_line(), and qqplotr::stat_qq_band().

Details

plot_qq() is a convenience wrapper around the qqplotr functions stat_qq_point(), stat_qq_line(), and stat_qq_band(). It is useful for checking whether values, residuals, or forecast errors approximately follow a theoretical distribution.

By default, the function creates a normal quantile-quantile plot with pointwise confidence bands.

The arguments x, facet_var, and color are passed as unquoted column names.

If color is supplied, point colors, line colors, and confidence-band fills are mapped to that variable. In this case, point_color, point_fill, line_color, and band_color are ignored. If color is not supplied, the fixed styling arguments are used.

Additional arguments can be passed to the underlying qqplotr statistics through ..., for example distributional arguments supported by qqplotr.

Additional theme settings can be supplied through theme_config. This should be a named list of arguments passed to ggplot2::theme().

Value

An object of class ggplot.

See Also

Other data visualization: plot_bar(), plot_density(), plot_histogram(), plot_line(), plot_point(), scale_color_tscv(), scale_fill_tscv(), theme_tscv(), tscv_cols(), tscv_pal()

Examples

library(dplyr)

data <- M4_monthly_data |>
  filter(series %in% c("M23100", "M14395"))

plot_qq(
  data = data,
  x = value,
  facet_var = series,
  title = "QQ Plot of M4 Monthly Values",
  subtitle = "Normal quantile-quantile plots by series",
  xlab = "Theoretical quantiles",
  ylab = "Sample quantiles"
)

stats <- data |>
  group_by(series) |>
  mutate(value_centered = value - mean(value, na.rm = TRUE)) |>
  ungroup()

plot_qq(
  data = stats,
  x = value_centered,
  color = series,
  title = "QQ Plot of Centered M4 Monthly Values",
  subtitle = "Normal quantile-quantile plots by series",
  xlab = "Theoretical quantiles",
  ylab = "Sample quantiles"
)

tscv documentation built on May 13, 2026, 9:07 a.m.