Computes Effective Sample Size Following Guemas et al, BAMS, 2013b
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, virginie.guemas at ic3.cat) - Original code
1.0 - 2013-09 (N. Manubens, nicolau.manubens at ic3.cat) - 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)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.