Eno | R Documentation |
Compute the number of effective samples along one dimension of an array. This
effective number of independent observations can be used in
statistical/inference tests.
The calculation is based on eno function from Caio Coelho from rclim.txt.
Eno(data, time_dim = "sdate", na.action = na.pass, ncores = NULL)
data |
A numeric array with named dimensions. |
time_dim |
A function indicating the dimension along which to compute the effective sample size. The default value is 'sdate'. |
na.action |
A function. It can be na.pass (missing values are allowed) or na.fail (no missing values are allowed). See details in stats::acf(). The default value is na.pass. |
ncores |
An integer indicating the number of cores to use for parallel computation. The default value is NULL. |
An array with the same dimension as parameter 'data' except the time_dim dimension, which is removed after the computation. The array indicates the number of effective sample along time_dim.
set.seed(1)
data <- array(rnorm(800), dim = c(dataset = 1, member = 2, sdate = 4,
ftime = 4, lat = 10, lon = 10))
na <- floor(runif(40, min = 1, max = 800))
data[na] <- NA
res <- Eno(data)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.