bell

lbell

These functions compute the Bell number (the number of partitions of a given
number of items) or its natural logarithm.

The SALSO algorithm is an efficient randomized greedy search method to find a point estimate for a random partition based on a loss function and posterior Monte Carlo samples. The algorithm is implemented for many loss functions, including the Binder loss and a generalization of the variation of information loss, both of which allow for unequal weights on the two types of clustering mistakes. Efficient implementations are also provided for Monte Carlo estimation of the posterior expected loss of a given clustering estimate. See Dahl, Johnson, Müller (2022) <doi:10.1080/10618600.2022.2069779>.

David B Dahl

salso

Search Algorithms and Loss Functions for Bayesian Clustering

David B. Dahl

Devin J. Johnson

Peter Müller

Andrés Felipe Barrientos

Garritt Page

David Dunson

Alex Crichton

Brendan Zabarauskas

David Tolnay

Jim Turner

Josh Stone

R. Janis Goldschmidt

Sean McArthur

Stefan Lankes

The Cranelift Project Developers 

The CryptoCorrosion Contributors 

The Rand Project Developers 

The Rust Project Developers 

Ulrik Sverdrup "bluss"

bluss 

bell function

<dl><dt>nItems</dt>
<dd>The size of the set \({1, 2, ..., n}\).</dd></dl>

Arguments

Compute the Bell Number — bell

<dl>

<dt>nItems</dt>
<dd>The size of the set \({1, 2, ..., n}\).</dd>

</dl>

Compute the Bell Number

bell: Compute the Bell Number

Description

Usage

Value

Arguments

Examples