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Create a quantile-quantile plot

Source: R/plot_qq.R
plot_qq.Rd

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().

Value

An object of class ggplot.

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().

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"
)