Man pages for btaschler/mcap
Model-Based Clustering in High Dimensions via Adaptive Projections
| CentrePerGroup | Centre a data matrix to mean zero (per group) |
| ClusterStability | Compute cluster stability of MCAP output |
| ComputeSEM | Compute standard error of the mean for an input vector |
| GMMwrapper | Wrapper to do clustering with Gaussian mixture models |
| GramPCA | Perform PCA using Gram matrix |
| HCLUSTwrapper | Wrapper to do hierarchical clustering |
| KMwrapper | Wrapper to do K-means clustering |
| mcap | mcap: Model-based clustering in very high dimensions via... |
| MCAPfit | Model based clustering via adaptive (linear) projections |
| OptDimClusterStability | Determine optimal projection dimension (PCA or random... |
| Precision2PartialCor | Compute partial correlation matrix from inverse covariance... |
| Rand1 | Return a random sign vector |
| RandProject | Random projection of input matrix X |
| Rank2Normality | Transform data matrix to normality based on rank |
| SPECTRALwrapper | Wrapper to do spectral clustering |
