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