asympTest: an R package for performing parametric statistical tests and confidence intervals based on the central limit theorem

Jean-François Coeurjolly (1) , Rémy Drouilhet (1) , Pierre Lafaye de Micheaux (1) , Jean-François Robineau (1)

1 SAGAG - Statistique Appliquée et de Géométrie Aléatoire de Grenoble

This paper describes an R package implementing large sample tests and confidence intervals (based on the central limit theorem) for various parameters. The one and two sample mean and variance contexts are considered. The statistics for all the tests are expressed in the same form, which facilitates their presentation. In the variance parameter cases, the asymptotic robustness of the classical tests depends on the departure of the data distribution from normality measured in terms of the kurtosis of the distribution.

Mots clés: R package; central limit theorem; confidence intervals; parametric tests

Domaines: Calcul [stat.CO]; Statistiques [math.ST]; Théorie [stat.TH]; Méthodologie [stat.ME]

Jean-François Coeurjolly, Rémy Drouilhet, Pierre Lafaye de Micheaux, Jean-François Robineau. asympTest: an R package for performing parametric statistical tests and confidence intervals based on the central limit theorem. 2009. ⟨hal-00358375v2⟩