EnoNew | R Documentation |
This function computes the effective number of independent values in the
xdata array following the method described in
Guemas V., Auger L., Doblas-Reyes F., JAMC, 2013. EnoNew
provides
similar functionality to Eno
but with the added options to remove
the linear trend or filter the frequency.
EnoNew(xdata, detrend = FALSE, filter = FALSE)
xdata |
A numeric vector. |
detrend |
Should the linear trend be removed from the data prior to the estimation of the equivalent number of independent values. |
filter |
Should a filtering of the frequency peaks be applied prior to the estimation of the equivalent number of independant data. |
History:
0.1 - 2012-06 (V. Guemas) - Original code
1.0 - 2013-09 (N. Manubens) - Formatting to CRAN
Guemas V, Auger L, Doblas-Reyes FJ, Rust H, Ribes A, 2014, Dependencies in Statistical Hypothesis Tests for Climate Time Series. Bulletin of the American Meteorological Society, 95 (11), 1666-1667.
# See examples on Load() to understand the first lines in this example ## Not run: data_path <- system.file('sample_data', package = 's2dverification') exp <- list( name = 'experiment', path = file.path(data_path, 'model/$EXP_NAME$/monthly_mean', '$VAR_NAME$_3hourly/$VAR_NAME$_$START_DATES$.nc') ) obs <- list( name = 'observation', path = file.path(data_path, 'observation/$OBS_NAME$/monthly_mean', '$VAR_NAME$/$VAR_NAME$_$YEAR$$MONTH$.nc') ) # Now we are ready to use Load(). startDates <- c('19851101', '19901101', '19951101', '20001101', '20051101') sampleData <- Load('tos', list(exp), list(obs), startDates, leadtimemin = 1, leadtimemax = 4, output = 'lonlat', latmin = 27, latmax = 48, lonmin = -12, lonmax = 40) ## End(Not run) eno <- EnoNew(sampleData$mod[1, 1, , 1, 2, 3]) print(eno)
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