miller.jack {nonpar}

The Miller Jackknife Procedure

Description

This function will perform Miller's Jackknife Procedure to test differences in scale between 2 samples. It is best for large samples.

Usage

miller.jack(x, y, alpha = NULL,
alternative =c("two.sided", "greater", "less"), exact = FALSE)

Arguments

x

A vector containing data from the first sample.

y

A vector containing data from the second sample.

alpha

The Significance level, defaults to 0.05.

alternative

Defaults to two.sided. Used to determine what type of test to run.

exact

Defaults to FALSE. Used to determine whether to run the exact procedure or a large sample approximation.

Value

J

The test statistic.

Significance Level

Returns the alpha value.

P-value

Returns the p-value from Miller's Jackknife Procedure.

Author(s)

D. Lukke Sweet

References

Wiley Series in Probability and Statistics: Nonparametric Statistical Methods (3rd Edition). (2013). John Wiley & Sons.

Examples

  ## Run Miller's Jackknife Procedure on the 2 vectors.
  miller.jack(x= c(6.2, 5.9, 8.9, 6.5, 8.6),
              y = c(9.5, 9.8, 9.5, 9.6, 10.3), alpha=0.05, alternative="less")