Description Usage Arguments Value Author(s) Source References Examples
CumulativeDeviations
returns the result (Q) of the
cumulative deviations test (parametric test for step jump in mean)
applied to a time series. CumulativeDeviationsQR
return Q, R
and abs(Q)/sqrt(N).
1 | CumulativeDeviations(dataSeries)
|
dataSeries |
vector with climate data |
The result of the cumulative deviations test.
Jose Gama
Chiew F. and Siriwardena L., 2005 CRC for Catchment Hydrology Trend 1.0.2 User Guide, chapter 4.2.11 Rank Difference Test, pp. 21 http://www.toolkit.net.au/Tools/TREND/documentation
Kundzewicz, Z.W. and Robson, A., 2000 Detecting Trend and Other Changes in Hydrological Data. World Climate Program - Water, WMO/UNESCO, WCDMP-45, WMO/TD 1013, Geneva, 157 pp.
Grayson, R.B., Argent, R.M., Nathan, R.J., McMahon, T.A. and Mein, R., 1996 Hydrological Recipes: Estimation Techniques in Australian Hydrology. Cooperative Research Centre for Catchment Hydrology, Australia, 125 pp.
Chiew F. and Siriwardena L., 2005 CRC for Catchment Hydrology Trend 1.0.2 User Guide, chapter 4.2.11 Rank Difference Test, pp. 21 http://www.toolkit.net.au/Tools/TREND/documentation
Kundzewicz, Z.W. and Robson, A., 2000 Detecting Trend and Other Changes in Hydrological Data. World Climate Program - Water, WMO/UNESCO, WCDMP-45, WMO/TD 1013, Geneva, 157 pp.
Grayson, R.B., Argent, R.M., Nathan, R.J., McMahon, T.A. and Mein, R., 1996 Hydrological Recipes: Estimation Techniques in Australian Hydrology. Cooperative Research Centre for Catchment Hydrology, Australia, 125 pp.
1 2 3 4 5 6 7 8 9 10 11 | # cumulative deviations for Turin 1961-2003
cdTurin<- CumulativeDeviations(yearly.average.temperature.Turin.Milan[,2])
# cumulative deviations for Milan 1961-2003
cdMilan<- CumulativeDeviations(yearly.average.temperature.Turin.Milan[,3])
plot(1961:2003,cdTurin,type='l',col='cyan',ylim=c(0,15),
main='Cumulative deviations 1961-2003',xlab='Years',ylab='C.D.')
par(new=TRUE)
plot(1961:2003,cdMilan,type='l',col='magenta',ylim=c(0,15),xlab='',ylab='')
legend("top",c('Turin','Milan'),text.col=c('cyan','magenta'))
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