asympTest: A simple R package for classical parametric statistical tests and confidence intervals in large samples

R Journal

Volumn 1, Issue 2, 2009, Pages 26-30

  Coeurjolly, J F ^a   Drouilhet, R ^a   Lafaye de Micheaux, P ^b   Robineau, J F ^c  

^a UNIV GRENOBLE ALPES   (France)

^b UNIVERSITÉ DE MONTRÉAL   (Canada)

^c CQLS   (France)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 79961171064     PISSN: None     EISSN: 20734859     Source Type: Journal    
DOI: 10.32614/rj-2009-015     Document Type: Article

References (14)

1. D. G. Bonnet. Approximate confidence interval for standard deviation of nonnormal distributions. Computational Statistics & Data Analysis, 50:775- 782, 2006.
2. D. G. Bonnet. Robust confidence interval for a ratio of standard deviations. Applied Psychological Measurement, 30:(5) 432-439, 2006.
3. G. E. P. Box. Non-normality and tests on variances. Biometrika, 40:(3/4) 318-335, 1953.
4. G. Casella and R. L. Berger. Statistical Inference. Duxbury Press, Belmont, California, 2nd edition, 2001.
5. J.-F. Coeurjolly, R. Drouilhet, P. Lafaye de Micheaux and J.-F. Robineau. asympTest: an R package for performing parametric statistical tests and confidence intervals based on the central limit theorem. Technical report, URL http://www.citebase.org/abstract?id=oai:arXiv.org:0902.0506.
6. W. J. Conover, M. E. Johnson and M. M. Johnson. A comparative study of tests for homogeneity of variances with applications to the outer continental shelf bidding data. Technometrics, 23:(4) 351- 361, 1981.
7. R. Davidson and J. G. MacKinnon. Graphical methods for investigating the size and power of hypothesis tests. The Manchester School, 66:(1) 1-26, 1998.
8. S. Dean and B. Illowsky. F Distribution and ANOVA: Test of Two Variances. Connexions, February 5, 2009. URL http://cnx.org/content/m17075/1.6/
9. T. Ferguson. A course in large sample theory. Chapman and Hall, 1996.
10. R. A. Fisher. The use of multiple measurements in taxonomic problems. Annals of Eugenics, 7:(Part II) 179-188, 1935.
11. R. G. Miller. Beyond ANOVA, Basics of Applied Statistics. Texts in Statistical Science Series. Chapman & Hall/CRC, 1997.
12. C. Ozgur and S. E. Strasser. A study of the statistical inference criteria: Can we agree on when to use z versus t? Decision Sciences Journal of Innovative Education, 2:(2) 177-192, 2004.
13. G. Pan. On a Levene type test for equality of two variances. Journal of Statistical Computation and Simulation, 63:59-71, 1999.
14. M. L. Tiku and A. Akkaya. Robust Estimation and Hypothesis Testing. New Age International (P) Ltd, New Delhi, 2004.