Two new classes of nonparametric tests for scale parameters

Testing of homogeneity of populations is a very useful phenomenon in several fields. After knowing that the two populations have the same variability or not, public/private sector organizations can execute their plans accordingly. In this paper, two new classes of nonparametric tests are proposed to test whether the scale parameters of two populations are the same or not. For each class of tests, we determine which member of the class provides the maximum efficacy; and compare its performance with some of the existing tests. Monte Carlo simulation study is carried to see the performance of both tests in terms of power. An illustrative example is also provided to see the implementation of the proposed tests.

• Publication year

  2020

• Venue

  Journal of Statistical Computation and Simulation

• Publication date

  2020-07-28

• Fields of study

  Mathematics

• Identifiers
  DOI 10.1080/00949655.2020.1797029
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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