Bootstrap t-test for 2 independent samples {Rfast}

Bootstrap t-test for 2 independent samples

Description

Bootstrap t-test for 2 independent samples.

Usage

boot.ttest2(x, y, B = 999)

Arguments

x

A numerical vector with the data.

y

A numerical vector with the data.

B

The number of bootstrap samples to use.

Details

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.

Value

A vector with the test statistic and the bootstrap p-value.

Author(s)

Michail Tsagris and Christina Chatzipantsiou

R implementation and documentation: Michail Tsagris <[e-mail]> and Christina Chatzipantsiou <[e-mail]>.

References

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

See Also

ttest2, exact.ttest2, ftest

Examples

tic <- proc.time()
x <- rexp(40, 4)
y <- rbeta(50, 2.5, 7.5)
a <- boot.ttest2(x, y, 9999)
a