If valid observations <= 5, NA will be returned.

mkTrend_r(y, ci = 0.95, IsPlot = FALSE)

mkTrend(y, x = seq_along(y), ci = 0.95, IsPlot = FALSE)

Arguments

y

numeric vector

ci

critical value of autocorrelation

IsPlot

boolean

x

(optional) numeric vector

Value

  • Z0 : The original (non corrected) Mann-Kendall test Z statistic.

  • pval0: The original (non corrected) Mann-Kendall test p-value

  • Z : The new Z statistic after applying the correction

  • pval : Corrected p-value after accounting for serial autocorrelation N/n*s Value of the correction factor, representing the quotient of the number of samples N divided by the effective sample size n*s

  • slp : Sen slope, The slope of the (linear) trend according to Sen test

Details

mkTrend is 4-fold faster with .lm.fit.

Note

slp is significant, if pval < alpha.

References

Hipel, K.W. and McLeod, A.I. (1994), Time Series Modelling of Water Resources and Environmental Systems. New York: Elsevier Science.

Libiseller, C. and Grimvall, A., (2002), Performance of partial Mann-Kendall tests for trend detection in the presence of covariates. Environmetrics 13, 71--84, doi:10.1002/env.507 .

See also

fume::mktrend and trend::mk.test

Author

Dongdong Kong

Examples

x <- c(4.81, 4.17, 4.41, 3.59, 5.87, 3.83, 6.03, 4.89, 4.32, 4.69)
r <- mkTrend(x)
r_cpp <- mkTrend(x, IsPlot = TRUE)