C++ implementation of the F-measure computation
C++ implementation of residual trace computation step used when sampling the scale
Return updated sufficient statistics S for skew t-distribution
with data matrix z
Slice Sampling of Dirichlet Process Mixture of Gaussian distibutions
Slice Sampling of the Dirichlet Process Mixture Model
with a prior on alpha
Generating cluster data from the Chinese Restaurant Process
DPMGibbsSkewT_SeqPrior_parallel
Slice Sampling of Dirichlet Process Mixture of skew Students's t-distibutions
MLE for Gamma distribution
C++ implementation of multivariate Normal probability density function
C++ implementation of multivariate skew Normal probability density function for multiple inputs
Plot of a Dirichlet process mixture of skew normal distribution partition
Compute a limited F-measure
Burning MCMC iterations from a Dirichlet Process Mixture Model.
EM MAP for mixture of sNiW
EM MLE for mixture of sNiW
Slice Sampling of Dirichlet Process Mixture of skew Students's t-distibutions
C++ implementation of multivariate Normal inverse Wishart probability density function for multiple inputs
ELoss of a partition point estimate compared to a gold standard
multivariate skew-t probability density function
Slice Sampling of Dirichlet Process Mixture of skew Students's t-distibutions
Convergence diagnostic plots
C++ implementation of the F-measure computation without the ref classe 0
Multiple cost computations with Fmeasure as the loss function
Methods for a summary of a 'DPMMclust' object
Gets a point estimate of the partition using posterior expected adjusted
Rand index (PEAR)
C++ implementation of multivariate Normal probability density function for multiple inputs
Sample from a inverse-Wishart distribution
Slice Sampling of Dirichlet Process Mixture of skew Students's t-distibutions
multivariate Student's t-distribution probability density function
C++ implementation
Probability density function of multiple structured Normal inverse Wishart
Construction of an Empirical based prior
C++ implementation of multivariate Normal probability density function for multiple inputs
C++ implementation of multivariate structured Normal inverse Wishart probability density function for multiple inputs
MLE for sNiW distributed observations
Slice Sampling of the Dirichlet Process Mixture Model with a prior on alpha
multivariate-Normal probability density function
Computes the coclustering (or similarity) matrix
multivariate Skew-Normal probability density function
Scatterplot of flow cytometry data
Post-processing Dirichlet Process Mixture Models results to get
a mixture distribution of the posterior locations
Return updated sufficient statistics S with new data matrix z
Multivariate log gamma function
Summarizing Dirichlet Process Mixture Models
Point estimate of the partition using a modified Binder loss function
C++ implementation
Sample from a Wishart distribution
C++ implementation of similarity matrix computation using precomputed distances
Posterior estimation for Dirichlet process mixture of multivariate (potentially skew) distibutions models
Parallel Implementation of Slice Sampling of Dirichlet Process Mixture of skew Normals
Bayesian Nonparametrics for Automatic Gating of Flow Cytometry data
Point estimate of the partition for the Binder loss function
multivariate Normal inverse Wishart probability density function for multiple inputs
Plot of a Dirichlet process mixture of skew t-distribution partition
Plot of a Dirichlet process mixture of gaussian distribution partition
C++ implementation of the multinomial sampling from a matrix
of column vectors, each containing the sampling probabilities
for their respective draw
Sample from a Normal inverse-Wishart distribution
whose parameter are given by the structure hyper
Sampler for the concentration parameter of a Dirichlet process
Return updated sufficient statistics S with new data matrix z
Slice Sampling of Dirichlet Process Mixture of skew normal ditributions
EM MLE for mixture of NiW
Point estimate of the partition using the F-measure as the cost function.
C++ implementation of multivariate Normal probability density function for multiple inputs
C++ implementation of multivariate Normal probability density function for multiple inputs
C++ implementation
Sample from a normal inverse Wishart distribution
whose parameter are given by the structure SufStat