Computes Effective Sample Size With Classical Method
Computes the effective number of independent values along the posdim
dimension of a matrix.
This effective number of independent observations can be used in
statistical/inference tests.
Based on eno function from Caio Coelho from rclim.txt.
Eno(obs, posdim)
obs |
Matrix of any number of dimensions up to 10. |
posdim |
Dimension along which to compute the effective sample size. |
Same dimensions as var but without the posdim dimension.
History:
0.1 - 2011-05 (V. Guemas, virginie.guemas at ic3.cat) - Original code
1.0 - 2013-09 (N. Manubens, nicolau.manubens at ic3.cat) - Formatting to R CRAN
# 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$.nc')
)
# Now we are ready to use Load().
startDates <- c('19851101', '19901101', '19951101', '20001101', '20051101')
sampleData <- Load('tos', list(exp), list(obs), startDates,
leadtimemin = 1, leadtimemax = 4, output = 'lonlat',
latmin = 27, latmax = 48, lonmin = -12, lonmax = 40)
## End(Not run)
sampleData$mod <- Season(sampleData$mod, 4, 11, 1, 12)
eno <- Eno(sampleData$mod[1, 1, , 1, , ], 1)
PlotEquiMap(eno, sampleData$lon, sampleData$lat)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.