Slope
Ipaper.slope_mk
— Functionslope_mk(y::AbstractVector, x::AbstractVector=1:length(y); ci=0.95)
Arguments
y
: numeric vectorx
: (optional) numeric vectorci
: critical value of autocorrelation
Return
Z0
: The original (non corrected) Mann-Kendall test Z statistic.pval0
: The original (non corrected) Mann-Kendall test p-valueZ
: The new Z statistic after applying the correctionpval
: Corrected p-value after accounting for serial autocorrelationN/n*s
Value of the correction factor, representing the quotient of the number of samples N divided by the effective sample sizen*s
slp
: Sen slope, The slope of the (linear) trend according to Sen test. 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.
Example
slope_mk([4.81, 4.17, 4.41, 3.59, 5.87, 3.83, 6.03, 4.89, 4.32, 4.69])
A = rand(100, 100, 30, 4)
@time r = mapslices(slope_mk, A; dims=3);
Ipaper.slope_p
— Functionslope_p(y::AbstractVector, x::AbstractVector=1:length(y))
Reference
- https://zhuanlan.zhihu.com/p/642186978
Example
x = [1, 2, 3, 4, 5];
y = [2, 4, 5, 4, 6];
slope_p(y)