Many researchers used time series (rainfall, temperature etc.) with varying length of records (say 30, 40, 50, 75, 100, 135 years) for analysing trends using well known Mann-Kendall test. Is it appropriate to use any length or is there any metric that can help in deciding optimal length of the time series for MK test.
You can go through the articles/paper
Trend analysis of annual and seasonal rainfall time series
in the Mediterranean area
Using Mann-Kendall and Time Series Techniques for Statistical
Analysis of Long-Term Precipitation in Gorgan Weather Station
Trend Analysis
Precipitation Trends over Time Using Mann-Kendall and Spearman’s rho Tests in Swat River Basin, Pakistan
Based on the calculation principle of MK test, I think the core step of the test is the hypothetical test of the rank. And the hypothetical test of the rank must obey the Law of Large Number. Accordithng to the Law of Large Number, the larger the sample size is, the better the hypothetical test is. And in hydrology and water resources, the sample size should be larger than 30. So I think the length of the time series shoule be longer than 30.
The empirical studies have proved the reliability of samples over 30-40 years. Actually there is not any formula, it is an experimental fact.
- Badges
- Science topic
- Similar topics
- Statistics
- Time Series