PBGoF-precomputed-tests: Fast Skew-Normal Goodness-of-Fit Tests Using Precomputed...

In PBGoF: Parametric Bootstrap Tests for the Skew-Normal Distribution

Fast Skew-Normal Goodness-of-Fit Tests Using Precomputed Quantiles

Description

Computes a skew-normal goodness-of-fit statistic and obtains an approximate p-value from a precomputed 100,000-replicate quantile table.

Usage

PBGoF_ks_test(data, ks_table = NULL)

PBGoF_cvm_test(data, cvm_table = NULL)

Arguments

data	A numeric vector whose length is represented in the table.
ks_table, cvm_table	Optional custom quantile tables. If NULL, the corresponding table bundled with PBGoF is used.

Details

The fitted absolute CP skewness is rounded to two decimal places and truncated to [0.01, 0.99]. P-values are conservative step-function approximations between 0.01 and 0.99. No interpolation is performed.

If the fitted gamma1 is negative, table lookup uses abs(gamma1). Reflection of a skew-normal variable changes the signs of the DP shape parameter and CP skewness, but the null distributions of the EDF statistics are invariant to this sign change (Mateu-Figueras et al., 2007). The bundled tables therefore require only non-negative skewness values.

For samples larger than 500, all observations remain in the fit and empirical distribution function, while the external statistic multiplier and table row use n_used = 500.

Value

A list containing statistic, actual sample size n, lookup and scaling sample size n_used, gamma1_hat, gamma1_used, and p.value.

References

Mateu-Figueras, G., Puig, P., and Pewsey, A. (2007). Goodness-of-fit tests for the skew-normal distribution when the parameters are estimated from the data. Communications in Statistics—Theory and Methods, 36(9), 1735–1755. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1080/03610920601126217")}

Examples

set.seed(123)
x <- sn::rsn(50, xi = 0, omega = 1, alpha = 3)
PBGoF_ks_test(x)
PBGoF_cvm_test(x)

PBGoF documentation built on Oct. 2, 2026, 5:09 p.m.