adtestWrapper {robCompositions}

Wrapper for Anderson-Darling tests

Description

A set of Anderson-Darling tests (Anderson and Darling, 1952) are applied as proposed by Aitchison (Aichison, 1986).

Usage

adtestWrapper(x, alpha = 0.05, R = 1000, robustEst = FALSE)

## S3 method for class 'adtestWrapper'
print(x, ...)

## S3 method for class 'adtestWrapper'
summary(object, ...)

Arguments

x

compositional data of class data.frame or matrix

alpha

significance level

R

Number of Monte Carlo simulations in order to provide p-values.

robustEst

logical

...

additional parameters for print and summary passed through

object

an object of class adtestWrapper for the summary method

Details

First, the data is transformed using the ‘ilr’-transformation. After applying this transformation

- all (D-1)-dimensional marginal, univariate distributions are tested using the univariate Anderson-Darling test for normality.

- all 0.5 (D-1)(D-2)-dimensional bivariate angle distributions are tested using the Anderson-Darling angle test for normality.

- the (D-1)-dimensional radius distribution is tested using the Anderson-Darling radius test for normality.

A print and a summary method are implemented. The latter one provides a similar output is proposed by (Pawlowsky-Glahn, et al. (2008). In addition to that, p-values are provided.

Value

res

a list including each test result

check

information about the rejection of the null hypothesis

alpha

the underlying significance level

info

further information which is used by the print and summary method.

est

“standard” for standard estimation and “robust” for robust estimation

Author(s)

Matthias Templ and Karel Hron

References

Anderson, T.W. and Darling, D.A. (1952) Asymptotic theory of certain goodness-of-fit criteria based on stochastic processes Annals of Mathematical Statistics, 23 193-212.

Aitchison, J. (1986) The Statistical Analysis of Compositional Data Monographs on Statistics and Applied Probability. Chapman and Hall Ltd., London (UK). 416p.

See Also

adtest, pivotCoord

Examples

data(machineOperators)
a <- adtestWrapper(machineOperators, R=50) # choose higher value of R
a
summary(a)