| Type: | Package |
| Title: | Bootstrap Tests for Equality of 2, 3, or 4 Population Variances |
| Version: | 0.1.5 |
| Author: | Dexter Cahoy |
| Maintainer: | Dexter Cahoy <dexter.cahoy@gmail.com> |
| Description: | Tests the hypothesis that variances are homogeneous or not using bootstrap. The procedure uses a variance-based statistic, and is derived from a normal-theory test. The test equivalently expressed the hypothesis as a function of the log contrasts of the population variances. A box-type acceptance region is constructed to test the hypothesis. See Cahoy (2010) \doi{10.1016/j.csda.2010.04.012}. |
| License: | GPL (≥ 3) |
| Encoding: | UTF-8 |
| Imports: | stats |
| RoxygenNote: | 7.2.3 |
| NeedsCompilation: | no |
| Packaged: | 2023-11-10 20:57:08 UTC; cahoyd |
| Repository: | CRAN |
| Date/Publication: | 2023-11-10 23:40:02 UTC |
Bootstrap test for equality of two (2) population variances
Description
Testing equality of two (2) population variances against the alternative that both variances are not equal.
Usage
equa2vartest(x1, x2, a, B)
Arguments
x1 |
first sample vector of data or observations |
x2 |
second sample vector of data or observations |
a |
significance level alpha |
B |
number of bootstrap samples. At least 500 is recommended. |
Value
list consisting of a non-numeric decision whether to reject the null hypothesis or not, the significance level, the number of bootstrap samples used, and the bootstrap P-value calculated using the Euclidean distance.
References
Cahoy, DO (2010), A Bootstrap Test For Equality Of Variances, Computational Statistics & Data Analysis, 54(10), 2306-2316. doi:10.1016/j.csda.2010.04.012
Examples
x1=sqrt(10)*runif(8, -sqrt(3), sqrt(3) )
x2=sqrt(1)*runif(8, -sqrt(3), sqrt(3) )
equa2vartest(x1,x2,0.05, 1000)
x1=sqrt(1)*rexp(8)
x2=sqrt(1)*rexp(8)
equa2vartest(x1,x2,0.01, 1000)
Bootstrap test for equality of three (3) population variances
Description
Testing equality of three (3) population variances against the alternative that all variances are unequal.
Usage
equa3vartest(x1, x2, x3, a, B)
Arguments
x1 |
first sample vector of data or observations |
x2 |
second sample vector of data or observations |
x3 |
third sample vector of data or observations |
a |
significance level alpha |
B |
number of bootstrap samples. At least 500 is recommended. |
Value
list consisting of a non-numeric decision whether to reject the null hypothesis or not, the significance level, the number of bootstrap samples used, and the bootstrap P-value calculated using the Euclidean distance.
References
Cahoy, DO (2010), A Bootstrap Test For Equality Of Variances, Computational Statistics & Data Analysis, 54(10), 2306-2316. doi:10.1016/j.csda.2010.04.012
Examples
x1=sqrt(10)*runif(10, -sqrt(3), sqrt(3) )
x2=sqrt(1)*runif(10, -sqrt(3), sqrt(3) )
x3=sqrt(1)*runif(10, -sqrt(3), sqrt(3) )
equa3vartest(x1,x2,x3, a=0.05, B=1000)
equa3vartest( rexp(10) ,rexp(10) ,rexp(10) , a=0.01, B=1000)
Bootstrap test for equality of four (4) population variances
Description
Testing equality of four (4) population variances against the alternative that all variances are not equal.
Usage
equa4vartest(x1, x2, x3, x4, a, B)
Arguments
x1 |
first sample vector of data or observations |
x2 |
second sample vector of data or observations |
x3 |
third sample vector of data or observations |
x4 |
fourth sample vector of data or observations |
a |
significance level alpha |
B |
number of bootstrap samples. At least 500 is recommended. |
Value
list consisting of a non-numeric decision whether to reject the null hypothesis or not, the significance level, the number of bootstrap samples used, and the bootstrap P-value calculated using the Euclidean distance.
References
Cahoy, DO (2010), A Bootstrap Test For Equality Of Variances, Computational Statistics & Data Analysis, 54(10), 2306-2316. doi:10.1016/j.csda.2010.04.012
Examples
x1=sqrt(10)*runif(10, -sqrt(3), sqrt(3) )
x2=sqrt(1)*runif(10, -sqrt(3), sqrt(3) )
x3=sqrt(1)*runif(10, -sqrt(3), sqrt(3) )
x4=sqrt(1)*runif(10, -sqrt(3), sqrt(3) )
equa4vartest(x1,x2,x3, x4, a=0.05, B=500)
equa4vartest(rexp(10) ,rexp(10) ,rexp(10) , rexp(10), a=0.01, B=1000)
testequavar Package
Description
Tests the hypothesis that 2, 3, or 4 population variances are homogeneous or not using bootstrap.
Details
Reference:
Cahoy (2010) doi:10.1016/j.csda.2010.04.012
Author(s)
Dexter Cahoy dexter.cahoy@gmail.com