Returns \(\alpha H_n = \alpha \sum_{i=1}^{n} 1 / i\), the expected
number of distinct features ("dishes") sampled by n customers
in a one-parameter Indian buffet process.
Usage
morie_gh_ibp_expected_dishes(n, alpha)
Arguments
- n
number of customers (positive integer)
- alpha
mass parameter of the Indian buffet process (positive)
Value
numeric scalar expected number of distinct features
References
Ghosal, S. and van der Vaart, A. (2017).
Fundamentals of Nonparametric Bayesian Inference.
Cambridge University Press.
Examples
morie_gh_ibp_expected_dishes(n = 10, alpha = 3)
#> [1] 8.786905
