Eno: Computes Effective Sample Size With Classical Method

In s2dverification: Set of Common Tools for Forecast Verification

Computes Effective Sample Size With Classical Method

Description

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.

Usage

Eno(obs, posdim)

Arguments

obs	Matrix of any number of dimensions up to 10.
posdim	Dimension along which to compute the effective sample size.

Value

Same dimensions as var but without the posdim dimension.

Author(s)

History:
0.1 - 2011-05 (V. Guemas) - Original code
1.0 - 2013-09 (N. Manubens) - Formatting to R CRAN

Examples

# 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)

s2dverification documentation built on April 20, 2022, 9:06 a.m.