Description Usage Arguments Details Value References Examples
View source: R/normal_assumption.R
Performs the Anderson-Darling-Test test for normality.
1 |
X |
a single numeric vector of data values. |
The Anderson-Darling tests the null hypothesis that a sample is drawn from a population that follows a particular distribution. For the Anderson-Darling test, the critical values depend on which distribution is being tested against. This function works for normal distributions
An htest object is returned. The critical value and the p-value are contained in the object.
Stephens, M. A. (1974). EDF Statistics for Goodness of Fit and Some Comparisons, Journal of the American Statistical Association, Vol. 69, pp. 730-737.
Stephens, M. A. (1976). Asymptotic Results for Goodness-of-Fit Statistics with Unknown Parameters, Annals of Statistics, Vol. 4, pp. 357-369.
Stephens, M. A. (1977). Goodness of Fit for the Extreme Value Distribution, Biometrika, Vol. 64, pp. 583-588.
Stephens, M. A. (1977). Goodness of Fit with Special Reference to Tests for Exponentiality , Technical Report No. 262, Department of Statistics, Stanford University, Stanford, CA.
Stephens, M. A. (1979). Tests of Fit for the Logistic Distribution Based on the Empirical Distribution Function, Biometrika, Vol. 66, pp. 591-595.
1 2 3 4 5 6 7 8 | ## Not run:
z <- rnorm(100)
olsdiagnosticR:::anderson_darling_test(X = z)
y <- rexp(100)
olsdiagnosticR:::anderson_darling_test(X = y)
## End(Not run)
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.