scatMat: Visualize your data with a scatterplot matrix

In abnormally-distributed/Bayezilla: Bayesian Models With JAGS and Several Utilities for Data Exploration and Model Evaluation.

Description

This is a function to help quickly visualize the relationships among your data. Like the other pre-themed plotting functions in this package, this utilizes a minimalist Tufte inspired aesthetic. When smooth is true it also automatically detects factor variables or variables with less than 4 unique values to avoid trying to fit a smooth line to nominal data, which is typically ugly at best and uninformative at worst.

Usage

scatMat(x, smooth = TRUE, digits = 2, method = "spearman",
  pch = 19, lm = FALSE, cor = TRUE, jitter = FALSE, amount = 2,
  hist.col = "#0054f9A6", points.col = "#35a8f59E",
  smooth.col = "#663399BF", breaks = "FD", cex.cor = 1,
  cex.num = 1.5, smoother = TRUE, font = "serif", ...)

Arguments

x	The data frame
smooth	Should the smoother line be enabled?
digits	Number of significant digits. defaults to 2.
method	method used for correlations; one of "pearson", "spearman" (the default), or "kendall"
pch	The symbol used for plotting
lm	TRUE or FALSE (Defaults to FALSE)
cor	TRUE or FALSE (Defaults to TRUE)
jitter	TRUE or FALSE (Defaults to FALSE)
amount	Amount of jittering
hist.col	The histogram color. Defaults to "#0054f9A6".
points.col	The color of the data points. Defaults to "#35a8f59E".
smooth.col	The color of the smooth line. Defaults to "#663399BF"
breaks	Breaks in histogram. Defaults to "FD" method.
cex.cor	Size of points
cex.num	The size of the numbers in the upper right triangle of the scatterplot. Defaults to 1.5
smoother	If TRUE, then smooth.scatter the data points – slow but pretty with lots of subjects
font	font for the axis labels. Defaults to "serif"
...	other arguments

Value

a plot

Examples

scatMat(iris)

abnormally-distributed/Bayezilla documentation built on Oct. 31, 2019, 1:57 a.m.