ScatterHist: Plot a scatter plot with marginals.

In WVPlots: Common Plots for Analysis

Plot a scatter plot with marginals.

Description

Plot a scatter plot with optional smoothing curves or contour lines, and marginal histogram/density plots. Based on https://win-vector.com/2015/06/11/wanted-a-perfect-scatterplot-with-marginals/. See also ggExtra::ggMarginal.

Usage

ScatterHist(
  frame,
  xvar,
  yvar,
  title,
  ...,
  smoothmethod = "lm",
  estimate_sig = FALSE,
  minimal_labels = TRUE,
  binwidth_x = NULL,
  binwidth_y = NULL,
  adjust_x = 1,
  adjust_y = 1,
  point_alpha = 0.5,
  contour = FALSE,
  point_color = "black",
  hist_color = "gray",
  smoothing_color = "blue",
  density_color = "blue",
  contour_color = "blue"
)

Arguments

frame	data frame to get values from
xvar	name of the independent (input or model) column in frame
yvar	name of the dependent (output or result to be modeled) column in frame
title	title to place on plot
...	no unnamed argument, added to force named binding of later arguments.
smoothmethod	(optional) one of 'auto', 'loess', 'gam', 'lm', 'identity', or 'none'.
estimate_sig	logical if TRUE and smoothmethod is 'identity' or 'lm', report goodness of fit and significance of relation.
minimal_labels	logical drop some annotations
binwidth_x	numeric binwidth for x histogram
binwidth_y	numeric binwidth for y histogram
adjust_x	numeric adjust x density plot
adjust_y	numeric adjust y density plot
point_alpha	numeric opaqueness of the plot points
contour	logical if TRUE add a 2d contour plot
point_color	color for scatter plots
hist_color	fill color for marginal histograms
smoothing_color	color for smoothing line
density_color	color for marginal density plots
contour_color	color for contour plots

Details

If smoothmethod is:

• 'auto', 'loess' or 'gam': the appropriate smoothing curve is added to the scatterplot.

• 'lm' (the default): the best fit line is added to the scatterplot.

• 'identity': the line x = y is added to the scatterplot. This is useful for comparing model predictions to true outcome.

• 'none': no smoothing line is added to the scatterplot.

If estimate_sig is TRUE and smoothmethod is:

• 'lm': the R-squared of the linear fit is reported.

• 'identity': the R-squared of the exact relation between xvar and yvar is reported.

Note that the identity R-squared is NOT the square of the correlation between xvar and yvar (which includes an implicit shift and scale). It is the coefficient of determination between xvar and yvar, and can be negative. See https://en.wikipedia.org/wiki/Coefficient_of_determination for more details. If xvar is the output of a model to predict yvar, then the identity R-squared, not the lm R-squared, is the correct measure.

If smoothmethod is neither 'lm' or 'identity' then estimate_sig is ignored.

Value

plot grid

See Also

ScatterHistC

Examples

if (requireNamespace('data.table', quietly = TRUE)) {
	# don't multi-thread during CRAN checks
		data.table::setDTthreads(1)
}

set.seed(34903490)
x = rnorm(50)
y = 0.5*x^2 + 2*x + rnorm(length(x))
frm = data.frame(x=x,y=y)
WVPlots::ScatterHist(frm, "x", "y",
  title= "Example Fit",
  smoothmethod = "gam",
  contour = TRUE)

if (FALSE) {
# Same plot with custom colors
WVPlots::ScatterHist(frm, "x", "y",
  title= "Example Fit",
  smoothmethod = "gam",
  contour = TRUE,
  point_color = "#006d2c", # dark green
  hist_color = "#6baed6", # medium blue
  smoothing_color = "#54278f", # dark purple
  density_color = "#08519c", # darker blue
  contour_color = "#9e9ac8") # lighter purple
}

WVPlots documentation built on Aug. 20, 2023, 9:07 a.m.