neuroca: multiblock component analysis for neuroimaging data

add_node | add a pre-processing stage |

bada | Barycentric Discriminant Analysis |

bi_projector | construct a 'bi-projector' instance |

block_apply | block_apply apply a function to each block of a multi-block... |

block_index_list | block_index_list |

block_lengths | block_lengths |

block_matrix | block_matrix |

block_matrix_list | block_matrix_list |

block_pca | block_pca |

block_project | project a single 'block' of data onto the subspace |

block_projector | #' projector_list projector_list <- function(Xs)... |

boot_ratio | compute bootstrap ratios for a list of matrices |

boot_sd | compute standard deviations for a set of bootstrap results |

bootstrap | bootstrap a model |

classifier | turn a model object into a classifier |

collapse | Column-wise average a matrix of variables, collapsing over... |

contributions | contributions |

cross_validate | cross_validate a model |

dim_reduce | dimension reduction as a pre-processing stage |

fast_estim_ncomp | fast_estim_ncomp |

fresh | get a fresh pre-processing node cleared of any cached data |

genpca | Generalized Principal Components Analysis |

get_block | get_block |

group_means | group_means |

hpca | hclust_pca |

loadings | loadings |

metapca | metapca |

mfa | multiple factor analysis |

muasca | muasca |

mubada | Multiple Subjects Barycentric Discriminant Analysis |

nblocks | nblocks extract the number of blocks in a mutli-block data... |

ncomp | ncomp get the number of components in the estimated model |

neuroca | neuroca - multivariate component analysis methods for... |

partial_project | project a selected subset of indices onto the subspace |

partial_projector | partial_projector |

partial_scores | partial_scores |

pca | principal components analysis |

prep | prepare a dataset by applying a pre-processing pipeline |

prepper | contains a series of pre-processing steps |

proc_rot | procrustes rotation |

project | project |

project_cols | project_cols |

projection_fun | projection_fun |

projector | construct a 'projector' instance |

project_table | project_table |

pseudo_svd | pseudo_svd |

reconstruct | reconstruct the data with some number of components |

reprocess.bi_projector | TODO is this needed |

reproducibility | reproducibility |

resample | resample data from a model fit |

residualize | Compute a regression model for each column in a matrix and... |

residuals | get the residuals of a model, after removing the first... |

rotate | apply a rotation matrix to a solution |

scada | scada |

scorepred | Given a set of projected scores and a set of reference... |

scores | scores |

shrink_pca | shrink_pca |

spatial_constraints | spatial constraints |

svd_wrapper | svd_wrapper |

trace_ratio | trace_ratio optimization |

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