A Nonparametric Trend Test for Seasonal Data With Serial Dependence

  title={A Nonparametric Trend Test for Seasonal Data With Serial Dependence},
  author={Robert M. Hirsch and James Richard Slack},
  journal={Water Resources Research},
Statistical tests for monotonic trend in seasonal (e.g., monthly) hydrologic time series are commonly confounded by some of the following problems: nonnormal data, missing values, seasonality, censoring (detection limits), and serial dependence. An extension of the Mann-Kendall test for trend (designed for such data) is presented here. Because the test is based entirely on ranks, it is robust against nonnormality and censoring. Seasonality and missing values present no theoretical or… 

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