Cramer_von_Mises_test: Cramer-von Mises Normality Test

In normality: Tests for Departure from Normality

Cramer-von Mises Normality Test

Description

An empirical distribution function (EDF)-based goodness-of-fit test that measures the overall discrepancy between the empirical and theoretical cumulative distribution functions by assigning relatively uniform weight across the entire distribution.

Usage

Cramer_von_Mises_test(
  x,
  alpha = 0.05,
  silent = FALSE,
  summary = TRUE,
  misc = FALSE
)

Arguments

x	A numeric vector, at least length of 8.
alpha	Numeric (default: 0.05). Significance threshold, range from 0 to 1.
silent	Logical (default: FALSE). If FALSE, print out the results.
summary	Logical (default: TRUE). Produce a summary table.
misc	Logical (default: FALSE). Output other unimportant parameters.

Value

A list.

References

Thode, H. C., Jr., 2002. Goodness of fit tests. Testing for normality. Marcel Dekker, New York. (Section 5.1.3, pg. 103)

Stephens, M.A., 2017. Tests Based on EDF Statistics. In: D'Agostino, R.B., Stephens, M.A. (Eds.), Goodness-of-Fit Techniques, 1st ed. Routledge, New York, (Table 4.9, pg. 127). https://doi.org/10.1201/9780203753064

Examples

out <- Cramer_von_Mises_test(rnorm(10))
print(out$summary)

normality documentation built on Aug. 23, 2026, 1:07 a.m.