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One and two sample mean and variance tests (differences and ratios) are considered. The test statistics are all expressed in the same form as the Student t-test, which facilitates their presentation in the classroom. This contribution also fills the gap of a robust (to non-normality) alternative to the chi-square single variance test for large samples, since no such procedure is implemented in standard statistical software.
| Version: | 0.1.4 |
| Depends: | R (≥ 1.8.0) |
| Published: | 2018-05-10 |
| Author: | Cqls Team |
| Maintainer: | Pierre Lafaye de Micheaux <lafaye at unsw.edu.au> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| URL: | https://www.r-project.org |
| NeedsCompilation: | no |
| Citation: | asympTest citation info |
| CRAN checks: | asympTest results |
| Reference manual: | asympTest.pdf |
| Package source: | asympTest_0.1.4.tar.gz |
| Windows binaries: | r-devel: asympTest_0.1.4.zip, r-release: asympTest_0.1.4.zip, r-oldrel: asympTest_0.1.4.zip |
| macOS binaries: | r-release (arm64): asympTest_0.1.4.tgz, r-oldrel (arm64): asympTest_0.1.4.tgz, r-release (x86_64): asympTest_0.1.4.tgz, r-oldrel (x86_64): asympTest_0.1.4.tgz |
| Old sources: | asympTest archive |
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