resampled_ttest {correctR}

Compute correlated t-statistic and p-value for resampled data

Description

Compute correlated t-statistic and p-value for resampled data

Usage

resampled_ttest(x, y, n, n1, n2, tailed = c("two", "one"), greater = NULL)

Arguments

x

numeric vector of values for model A

y

numeric vector of values for model B

n

integer denoting number of repeat samples. Defaults to length(x)

n1

integer denoting train set size

n2

integer denoting test set size

tailed

character denoting whether to perform a two-tailed or one-tailed test. Can be one of "two" or "one". Defaults to "two"

greater

character specifying whether "x" or "y" is greater for the one-tailed test if tailed = "one". Defaults to NULL

Value

data.frame containing the test statistic and p-value

Author(s)

Trent Henderson

References

Nadeau, C., and Bengio, Y. Inference for the Generalization Error. Machine Learning 52, (2003).

Bouckaert, R. R., and Frank, E. Evaluating the Replicability of Significance Tests for Comparing Learning Algorithms. Advances in Knowledge Discovery and Data Mining. PAKDD 2004. Lecture Notes in Computer Science, 3056, (2004).

Examples

x <- rnorm(100, mean = 95, sd = 0.5)
y <- rnorm(100, mean = 90, sd = 1)
resampled_ttest(x = x, y = y, n = 100, n1 = 80, n2 = 20, tailed = "two")