scagnostics {binostics} | R Documentation |
Scagnostics summarize potentially interesting patterns in 2d scatterplot
scagnostics(x, ...) ## Default S3 method: scagnostics(x, y, bins = 50, outlierRmv = TRUE, ...) ## S3 method for class 'matrix' scagnostics(x, ...) ## S3 method for class 'data.frame' scagnostics(x, ...) scagnostics_2d(x, ...)
x, y |
object to calculate scagnostics on: a vector, a matrix or a data.frame |
... |
Extra arguments |
bins |
number of bins, default=50 |
outlierRmv |
logical for trimming data, default=TRUE |
Current scagnostics are:
Outlying
Skewed
Clumpy
Sparse
Striated
Convex
Skinny
Stringy
Monotonic
These are described in more detail in: Graph-Theoretic Scagnostics, Leland Wilkinson, Anushka Anand, Robert Grossman. http://papers.rgrossman.com/proc-094.pdf
You can call the function with two 1d vectors to get a single vector of scagnostics, or with a 2d structure (matrix or data frame) to get scagnostics for every combination of the variables.
scagnostics(1:10, 1:10) scagnostics(rnorm(100), rnorm(100)) scagnostics(mtcars) scagnostics(as.matrix(mtcars))