| nclass {graphics} | R Documentation |
Compute the Number of Classes for a Histogram
Description
Compute the number of classes for a histogram, for use internally in
hist.
Usage
nclass.Sturges(x)
nclass.scott(x)
nclass.FD(x)
Arguments
x |
A data vector. |
Details
nclass.Sturges uses Sturges' formula, implicitly basing bin
sizes on the range of the data.
nclass.scott uses Scott's choice for a normal distribution based on
the estimate of the standard error.
nclass.FD uses the
Freedman-Diaconis choice based on the inter-quartile range.
Value
The suggested number of classes.
References
Venables, W. N. and Ripley, B. D. (2002) Modern Applied Statistics with S-PLUS. Springer, page 112.
Freedman, D. and Diaconis, P. (1981)
On the histogram as a density estimator: L_2 theory.
Zeitschrift für Wahrscheinlichkeitstheorie
und verwandte Gebiete 57, 453–476.
Scott, D. W. (1979) On optimal and data-based histograms. Biometrika 66, 605–610.
Scott, D. W. (1992) Multivariate Density Estimation. Theory, Practice, and Visualization. Wiley.
See Also
hist