Description Usage Arguments Value References See Also Examples
Dependency detection between a level k (k > 1) categorical variable x
and a continuous variable y
via Bayes factor with O(n^{1/2})resolution. The basic idea is almost the same as bfslice_u
. The only different is that bfslice_eqp_u
groups samples into approximate O(n^{1/2}) groups which contain approximate O(n^{1/2}) samples and treat the groups as a sample to calculate Bayes facor.
1  bfslice_eqp_u(x, dim, lambda, alpha)

x 
Vector: observations of categorical variable, 0,1,…,k1 for level k categorical variable, should be ranked according to values of continuous variable 
dim 
Level of 
lambda 

alpha 

Value of Bayes factor (nonnegative). Bayes factor could be treated as a statistic and one can take some threshold then calculates the corresponded Type I error rate. One can also take the value of Bayes factor for judgement.
Jiang, B., Ye, C. and Liu, J.S. Bayesian nonparametric tests via sliced inverse modeling. Bayesian Analysis, 12(1): 89112, 2017.
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