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Anderson-Darling Normality Test

Source: R/Anderson_Darling_test.R
Anderson_Darling_test.Rd

Performs the Anderson–Darling (A2) normality test, an EDF-based goodness-of-fit test that gives greater weight to deviations in the tails of the distribution.

Usage

Anderson_Darling_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

D’Agostino, R.B., 2017. Tests for the Normal Distribution. In: D'Agostino, R.B., Stephens, M.A. (Eds.), Goodness-of-Fit Techniques, 1st ed. Routledge, New York, pg. 372–373. https://doi.org/10.1201/9780203753064

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 4.8 & 4.9) pg. 126–128. https://doi.org/10.1201/9780203753064

Anderson, T.W., Darling, D.A., 1954. A Test of Goodness of Fit. J. Am. Stat. Assoc. 49, 765–769. https://doi.org/10.1080/01621459.1954.10501232

Examples

out <- Anderson_Darling_test(rnorm(10))
#> 
#> ------------------------------------
#> Anderson-Darling (A2) normality test 
#> 
#> Statistic (A2) = 0.3621 
#> p-value = 0.36758
#> ------------------------------------
print(out$summary)
#>                       alpha statistic      pval signif standard_value
#> Anderson-Darling (A2)  0.05 0.3621118 0.3675821     ns      0.3974177
#>                       critical_value SE CI_lower CI_upper  N        AVG
#> Anderson-Darling (A2)      0.6849762 NA       NA       NA 10 -0.4413645
#>                              MED       MIN      MAX       SD
#> Anderson-Darling (A2) -0.2457625 -2.437264 1.148412 1.117661