| NPflow-package | Bayesian Nonparametrics for Automatic Gating of Flow Cytometry data |
| burn.DPMMclust | Burning MCMC iterations from a Dirichlet Process Mixture Model. |
| cluster_est_binder | Point estimate of the partition for the Binder loss function |
| cluster_est_Fmeasure | Point estimate of the partition using the F-measure as the cost function. |
| cluster_est_Mbinder_norm | Point estimate of the partition using a modified Binder loss function |
| cluster_est_pear | Gets a point estimate of the partition using posterior expected adjusted Rand index (PEAR) |
| cytoScatter | Scatterplot of flow cytometry data |
| DPMGibbsN | Slice Sampling of the Dirichlet Process Mixture Model with a prior on alpha |
| DPMGibbsN_parallel | Slice Sampling of the Dirichlet Process Mixture Model with a prior on alpha |
| DPMGibbsN_SeqPrior | Slice Sampling of Dirichlet Process Mixture of Gaussian distributions |
| DPMGibbsSkewN | Slice Sampling of Dirichlet Process Mixture of skew normal distributions |
| DPMGibbsSkewN_parallel | Parallel Implementation of Slice Sampling of Dirichlet Process Mixture of skew normal distributions |
| DPMGibbsSkewT | Slice Sampling of Dirichlet Process Mixture of skew Student's t-distributions |
| DPMGibbsSkewT_parallel | Slice Sampling of Dirichlet Process Mixture of skew Student's t-distributions |
| DPMGibbsSkewT_SeqPrior | Slice Sampling of Dirichlet Process Mixture of skew Student's t-distributions |
| DPMGibbsSkewT_SeqPrior_parallel | Slice Sampling of Dirichlet Process Mixture of skew Student's t-distributions |
| DPMpost | Posterior estimation for Dirichlet process mixture of multivariate (potentially skew) distributions models |
| evalClustLoss | ELoss of a partition point estimate compared to a gold standard |
| Flimited | Compute a limited F-measure |
| FmeasureC | C++ implementation of the F-measure computation |
| FmeasureC_no0 | C++ implementation of the F-measure computation without the reference class 0 |
| Fmeasure_costC | Multiple cost computations with the F-measure as the loss function |
| lgamma_mv | Multivariate log gamma function |
| MAP_sNiW_mmEM | EM MAP for mixture of sNiW |
| MAP_sNiW_mmEM_vague | EM MAP for mixture of sNiW |
| MAP_sNiW_mmEM_weighted | EM MAP for mixture of sNiW |
| MLE_gamma | MLE for Gamma distribution |
| MLE_NiW_mmEM | EM MLE for mixture of NiW |
| MLE_sNiW | MLE for sNiW distributed observations |
| MLE_sNiW_mmEM | EM MLE for mixture of sNiW |
| mmNiWpdf | multivariate Normal inverse Wishart probability density function for multiple inputs |
| mmNiWpdfC | C++ implementation of multivariate Normal inverse Wishart probability density function for multiple inputs |
| mmsNiWlogpdf | Probability density function of multiple structured Normal inverse Wishart |
| mmsNiWpdfC | C++ implementation of multivariate structured Normal inverse Wishart probability density function for multiple inputs |
| mmvnpdfC | C++ implementation of multivariate Normal probability density function for multiple inputs |
| mmvsnpdfC | C++ implementation of multivariate skew Normal probability density function for multiple inputs |
| mmvstpdfC | C++ implementation of multivariate Normal probability density function for multiple inputs |
| mmvtpdfC | C++ implementation of multivariate Normal probability density function for multiple inputs |
| mvnlikC | C++ implementation of multivariate Normal probability density function for multiple inputs |
| mvnpdf | multivariate-Normal probability density function |
| mvnpdfC | C++ implementation of multivariate normal probability density function for multiple inputs |
| mvsnlikC | C++ implementation of multivariate skew normal likelihood function for multiple inputs |
| mvsnpdf | multivariate Skew-Normal probability density function |
| mvstlikC | C++ implementation of multivariate skew t likelihood function for multiple inputs |
| mvstpdf | multivariate skew-t probability density function |
| mvtpdf | multivariate Student's t-distribution probability density function |
| NPflow | Bayesian Nonparametrics for Automatic Gating of Flow Cytometry data |
| NuMatParC | C++ implementation of similarity matrix computation using pre-computed distances |
| plot.summaryDPMMclust | Methods for a summary of a 'DPMMclust' object |
| plot_ConvDPM | Convergence diagnostic plots |
| plot_DPM | Plot of a Dirichlet process mixture of gaussian distribution partition |
| plot_DPMsn | Plot of a Dirichlet process mixture of skew normal distribution partition |
| plot_DPMst | Plot of a Dirichlet process mixture of skew t-distribution partition |
| postProcess.DPMMclust | Post-processing Dirichlet Process Mixture Models results to get a mixture distribution of the posterior locations |
| print.summaryDPMMclust | Methods for a summary of a 'DPMMclust' object |
| priormix | Construction of an Empirical based prior |
| rCRP | Generating cluster data from the Chinese Restaurant Process |
| sample_alpha | Sampler for the concentration parameter of a Dirichlet process |
| similarityMat | Computes the co-clustering (or similarity) matrix |
| similarityMatC | C++ implementation |
| similarityMat_nocostC | C++ implementation |
| summary.DPMMclust | Summarizing Dirichlet Process Mixture Models |
| summaryDPMMclust | Methods for a summary of a 'DPMMclust' object |
| vclust2mcoclustC | C++ implementation |