Description Usage Arguments Value Examples
View source: R/homogeneous_GoF.R
creates equidistant bins based on hyper then calculates p-value based on chi and also based on empirical
1 | hyper_gof_test(data, m, n, k, n_sims = NA, trace = FALSE)
|
m |
number of success in proposed hypergeom |
n |
number of failures in proposed hypergeom |
k |
sample size of hypergeom |
n_sims |
is number of sims for empirical p-value |
list is both p-values and data frame of observed and expected freq so that can plot. Class is 'gof'
1 2 3 4 5 | data = rhyper(nn = 1000,m = 500,n = 500,k = 200)
gof = hyper_gof_test(data,m = 500,n = 500,k = 200)
print(gof)
gof = hyper_gof_test(data,m = 500,n = 500,k = 200, n_sims = 100)
print(gof)
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