R: Bootstrap t-test for 2 independent samples

Bootstrap t-test for 2 independent samples {Rfast} | R Documentation

## 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 √{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 <mtsagris@uoc.gr> and Christina Chatzipantsiou <chatzipantsiou@gmail.com>.

### 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)
    system.time( a <- boot.ttest2(x, y, 9999) )
    a

[Package Rfast version 2.0.4 Index]