mean: Inference for the Mean via Permutations
In astamm/piscalar: Permutation Inference for Scalar-Valued Data

Description Usage Arguments Value Examples

Performs statistical inference tasks (point estimation, confidence interval, tests) for the mean of the distributions of scalar-valued data.

t_test(
  x,
  y = NULL,
  alternative = c("two_tail", "left_tail", "right_tail"),
  mu = 0,
  paired = FALSE,
  var_equal = FALSE,
  conf_level = 0.95,
  B = 1000
)

wilcox_test(
  x,
  y = NULL,
  alternative = c("two_tail", "left_tail", "right_tail"),
  mu = 0,
  paired = FALSE,
  conf_level = 0.95,
  B = 1000L
)

`x`	A numeric vector providing the first sample.
`y`	A numeric vector providing the second sample.
`alternative`	A string specifying the type of alternative hypothesis. Choices are `"two_tail"`, `"left_tail"` or `"right_tail"`. Defaults to `"tow_tail"`.
`mu`	A numeric value providing the value of the mean difference `mu_y - mu_x` under the null hypothesis. Defaults to `0`.
`paired`	A boolean specifying whether the two samples are paired. Defaults to `FALSE`. Unused at the moment since one-sample tests are not yet available.
`conf_level`	A numeric value specifying the confidence level for the computation of a confidence interval for the mean difference. Defaults to `95%`.
`B`	An integer specifying the number of permutations to use. Defaults to `1000L`.

A list with class "htest" containing the following components:

statistic: the value of the test statistic computed from the original observed samples.
parameter: the degrees of freedom of the null distribution of the test statistic (not available for permutation tests).
p.value: the p-value for the test.
estimate: the estimated mean or mean difference mu_y - mu_x depending on whether it was a one-sample test, a paired two-sample test or an independent two-sample test.
conf.int: a confidence interval for the mean of for the mean difference appropriate to the specified alternative hypothesis.
null.value: the specified hypothesized value of the mean or mean difference depending on whether it was a one-sample test or a two-sample test.
stderr: an estimate of the standard deviation of the estimator of the mean or mean difference.
alternative: a string describing the alternative hypothesis.
method: a string indicating what type of test was performed.
data.name: a string giving the name(s) of the data.

x <- rnorm(10)
y <- rnorm(10)
z <- rnorm(10, mean = 3)
t1 <- t_test(x, y, B = 100)
t2 <- t_test(x, z, B = 100)
w1 <- wilcox_test(x, y, B = 100)
w2 <- wilcox_test(x, z, B = 100)