Two-sample similarity test for the expected value of random intervals. (English) Zbl 1422.62026
Ferraro, Maria Brigida (ed.) et al., Soft methods for data science. Selected papers based on the presentations at the 8th international conference on soft methods in probability and statistics, SMPS 2016, Rome, Italy, September 12–14, 2016. Cham: Springer. Adv. Intell. Syst. Comput. 456, 423-430 (2017).
Summary: The similarity degree between the expectation of two random intervals is studied by means of a hypothesis testing procedure. For this purpose, a similarity measure for intervals is introduced based on the so-called Jaccard index for convex sets. The measure ranges from 0 (if both intervals are not similar at all, i.e., if they are not overlapped) to 1 (if both intervals are equal). A test statistic is proposed and its limit distribution is analyzed by considering asymptotic and bootstrap techniques. Some simulation studies are carried out to examine the behaviour of the approach.
For the entire collection see [Zbl 1355.62005].
For the entire collection see [Zbl 1355.62005].
MSC:
| 62-07 | Data analysis (statistics) (MSC2010) |
| 62B15 | Theory of statistical experiments |
| 62N01 | Censored data models |
| 62G10 | Nonparametric hypothesis testing |
| 62F40 | Bootstrap, jackknife and other resampling methods |
Keywords:
two-sample similarity test; expected value; random intervals; hypothesis testing procedure; bootstrap; censored dataReferences:
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