rkt-package: Mann-Kendall Test, Seasonal and Regional Kendall Tests

Description Details Author(s) References Examples

Description

Contains function rkt which computes the Mann-Kendall test (MK) and the Seasonal and the Regional Kendall Tests for trend (SKT and RKT) and Theil-Sen's slope estimator.

Details

Package: rkt
Type: Package
Version: 1.5
Date: 2016-03-07
License: GPL-2

This function computes the Mann-Kendall test (MK) and the Seasonal and the Regional Kendall Tests for trend (SKT and RKT) and Sen's slope estimator.
MK, SKT and RKT are tests for monotonic trend in time series based on the Kendall rank correlation.
SKT and RKT are intrablock tests in which test statistics are computed for each season or month (SKT) or for each site (RKT) and combined in an overall test.
In RKT, seasonality can be accounted for by using a blocking variable combining both sites and seasons, such as (site * 12 + month).
When a covariable is defined, this function also computes partial RKT and SKT.
To allow for non-regular sampling dates, input data should be vectors, not time series.

Author(s)

Maintainer: Aldo Marchetto <[email protected]>

References

Marchetto A., Rogora M., Arisci S. 2013 Trend analysis of atmospheric deposition data: a comparison of statistical approaches. Atmospheric Environment 64, 95–102

Helsel D.R., Frans L.M. 2006 The regional Kendall test for trend: Environmental Science and Technology 40, 4066–4073

Helsel D.R., Mueller D.K., Slack J.R. 2006 Computer program for the Kendall family of trend tests U.S. Geological Survey Scientific Investigations Report 2005-5275, 4 pp.

Hirsch R.M., Slack J.R., Smith R.A. Techniques of trend ananlyis for monthly water quality data. Water Resources Research 18, 107-121

Hirsch R.M., Slack J.R. 1984 A nonparametric test for seasonal data with serial dependance. Water Resources Research 20, 727-732

Libiseller C., Grimvall A. 2002 Perfomance of partial Mann-Kendall tests for trend detection in the presence of covariates. Environmetrics 13, 71-84

Mann H.B. 1945. Nonparametric tests against trend. Econometrica 13, 245-249

Examples

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#
# monthly data, using covariate and intra-block correction
#
data(pie1)
ex<-rkt(pie1$Year,pie1$SO4,pie1$Month,pie1$mm,TRUE)
print(ex)
#
# weekly data, no intrablock correction
#
data(pie1w)
ex<-rkt(pie1w$Date,pie1w$SO4)
print(ex)
#
# monthly data, hydrological years (oct-sep) as in USGS program
#
data(pie1)
ex<-rkt(pie1$Year+floor(pie1$Month/10),pie1$SO4,pie1$Month,,TRUE)
print(ex)
#

Example output

Standard model
Tau = -0.3963554
Score =  -348
var(Score) =  2958.667
2-sided p-value =  1.777556e-10
Theil-Sen's (MK) or seasonal/regional Kendall (SKT/RKT) slope=  -0.09266667

Correction for inter-block covariance
var(Score) =  14495.33
2-sided p-value =  0.003949817

Partial model
Partial score =  -325.6001
var(Partial score) =  2532.056
2-sided p-value =  1.112785e-10

Correction for inter-block covariance
var(Score) =  8793.304
2-sided p-value =  0.0005370432

Standard model
Tau = -0.06411917
Score =  -1188
var(Score) =  804868.7
2-sided p-value =  0.1858066
Theil-Sen's (MK) or seasonal/regional Kendall (SKT/RKT) slope=  -0.06814002

Standard model
Tau = -0.3963554
Score =  -348
var(Score) =  2958.667
2-sided p-value =  1.777556e-10
Theil-Sen's (MK) or seasonal/regional Kendall (SKT/RKT) slope=  -0.09266667

Correction for inter-block covariance
var(Score) =  11434.67
2-sided p-value =  0.001174413

rkt documentation built on May 29, 2017, 6:59 p.m.