Bootstrap t-test for 2 independent samples
Bootstrap t-test for 2 independent samples.
boot.ttest2(x, y, B = 999)
x |
A numerical vector with the data. |
y |
A numerical vector with the data. |
B |
The number of bootstrap samples to use. |
Instead of sampling B times from each sample, we sample sqrt{B} from each of them and then take all pairs. Each bootstrap sample is independent of each other, hence there is no violation of the theory.
A vector with the test statistic and the bootstrap p-value.
Michail Tsagris and Christina Chatzipantsiou
R implementation and documentation: Michail Tsagris <mtsagris@yahoo.gr> and Christina Chatzipantsiou <chatzipantsiou@gmail.com>.
B.L. Welch (1951). On the comparison of several mean values: an alternative approach. Biometrika, 38(3/4), 330-336.
Efron Bradley and Robert J. Tibshirani (1993). An introduction to the bootstrap. New York: Chapman \& Hall/CRC.
Chatzipantsiou C., Dimitriadis M., Papadakis M. and Tsagris M. (2019). Extremely efficient permutation and bootstrap hypothesis tests using R. To appear in the Journal of Modern Applied Statistical Methods.
https://arxiv.org/ftp/arxiv/papers/1806/1806.10947.pdf
tic <- proc.time() x <- rexp(40, 4) y <- rbeta(50, 2.5, 7.5) system.time( a <- boot.ttest2(x, y, 9999) ) a
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