Ledermann

<p>Integer number of variables in data set.</p>

<p>Returns the maximum possible number of latent factors in a factor analysis model for data of dimension <code>P</code>. This Ledermann bound is given by the largest integer smaller than or equal to the solution \(k\) of \((M - k)^2 \geq M + k\).</p>

Provides flexible Bayesian estimation of Infinite Mixtures of Infinite Factor Analysers and related models, for nonparametrically clustering high-dimensional data, introduced by Murphy et al. (2017) <arXiv:1701.07010>. The IMIFA model conducts Bayesian nonparametric model-based clustering with factor analytic covariance structures without recourse to model selection criteria to choose the number of clusters or cluster-specific latent factors, mostly via efficient Gibbs updates. Model-specific diagnostic tools are also provided, as well as many options for plotting results and conducting posterior inference on parameters of interest.

Ledermann: Ledermann Bound

Description

Usage

Arguments

Value

Examples