Extending the Mann-Kendall test to allow for measurement uncertainty

Autor:	Stavros Nikolakopoulos, Eric Cator, Mart P. Janssen
Rok vydání:	2023
Předmět:	Statistics and Probability Methodology (stat.ME) FOS: Computer and information sciences FOS: Mathematics Mathematics - Statistics Theory Statistics Theory (math.ST) Statistics Probability and Uncertainty Statistics - Methodology Mathematics
Zdroj:	Statistics, 57, 577-596 Statistics, 57, 3, pp. 577-596
ISSN:	0233-1888
DOI:	10.1080/02331888.2023.2214942
Popis:	The Mann-Kendall test for trend has gained a lot of attention in a range of disciplines, especially in the environmental sciences. One of the drawbacks of the Mann-Kendall test when applied to real data is that no distinction can be made between meaningful and non-meaningful differences in subsequent observations. We introduce the concept of partial ties, which allows inferences while accounting for (non)meaningful difference. We introduce the modified statistic that accounts for such a concept and derive its variance estimator. We also present analytical results for the behavior of the test in a class of contiguous alternatives. Simulation results which illustrate the added value of the test are presented. We apply our extended version of the test to some real data concerning blood donation in Europe. Comment: 19 pages, 1 figure
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cf46e135269d738667a40011004ca1fa https://doi.org/10.1080/02331888.2023.2214942 Zobrazit plný text záznamu