sim.data

<p>This is a small dataset of 500 observations according to the \(\beta_{jk}\) parameterization. The number of reference variables is 1 and correspond to the values in the first column of the array <code>sim.data</code>. The number of response variables is 6 and correspond to the values in the last 6 column of the array <code>sim.data</code>. There are \(J=3\) conditions, while the number of replicates per condition is \(L=(3,2,1)\).</p>

datasets

Mixtures of Poisson Generalized Linear Models for high dimensional count data clustering. The (multivariate) responses can be partitioned into set of blocks. Three different parameterizations of the linear predictor are considered. The models are estimated according to the EM algorithm with an efficient initialization scheme <doi:10.1016/j.csda.2014.07.005>.

Panagiotis Papastamoulis

poisson.glm.mix

Fit High Dimensional Mixtures of Poisson GLMs

sim.data function

<p>A numeric array (sim.data) containing \(500\times 7\) observations.</p>

sim.data: Simulated data set of 500 observations

Description

Usage

Arguments

Format