nclass.numpy: Compute the Number of Classes for a Histogram

In ppgmmga: Projection Pursuit Based on Gaussian Mixtures and Evolutionary Algorithms

Compute the Number of Classes for a Histogram

Description

Compute the number of classes for a histogram as the maximum of the "Sturges" and "FD" (Freedman Diaconis) estimators as in numpy library for Python.

Usage

nclass.numpy(x, ...)

Arguments

x	A vector of values.
...	Further arguments passed to or from other methods.

Author(s)

Scrucca L. [e-mail]

See Also

nclass.Sturges, nclass.FD

Examples

## Not run: 
library(ggplot2)
x <- rnorm(100)
ggplot() + geom_histogram(aes(x), col = "grey92", bins = nclass.numpy(x))
x <- rnorm(1000)
ggplot() + geom_histogram(aes(x), col = "grey92", bins = nclass.numpy(x))
n = c(50, seq(100,1000,by=100))
brks = rep(NA, length(n))
for(i in seq(n)) brks[i] = nclass.numpy(rnorm(n[i]))
ggplot() + geom_point(aes(x = n, y = brks))

## End(Not run)

ppgmmga documentation built on Nov. 18, 2023, 1:12 a.m.