Package index • adjoin

All functions

adjacency(): Extract Adjacency Matrix from Graph Objects
adjacency(<neighbor_graph>): Extract adjacency matrix from neighbor_graph object
adjacency(<nn_search>): Create Adjacency Matrix from nnsearch Object
between_class_neighbors(): Between-Class Neighbors
between_class_neighbors(<class_graph>): Between-Class Neighbors for class_graph Objects
bilateral_smoother(): Bilateral Spatial Smoother
binary_label_matrix(): Create a Binary Label Adjacency Matrix (All Pairs)
class_graph(): Construct a Class Graph
class_means(): Class Means
class_means(<class_graph>): Class Means for class_graph Objects
commute_time_distance(): Compute the commute-time distance between nodes in a graph
compute_diffusion_kernel(): Compute Markov diffusion kernel via eigen decomposition
compute_diffusion_map(): Diffusion map embedding and distance
convolve_matrix(): Convolve a Data Matrix with a Kernel Matrix
cross_adjacency(): Cross Adjacency
cross_spatial_adjacency(): Cross Spatial Adjacency
cross_weighted_spatial_adjacency(): Cross-adjacency matrix with feature weighting
design_kernel(): Build a flexible design-similarity kernel
diagonal_label_matrix(): Create a Diagonal Label Comparison Matrix (Element-wise)
diagonal_label_matrix_na(): Diagonal Label Comparison with NA Handling
difference_of_gauss(): Compute the Difference of Gaussians for a coordinate matrix
discriminating_distance(): Compute Discriminating Distance for Similarity Graph
discriminating_similarity(): Compute Similarity Graph Weighted by Class Structure
dist_to_sim(<Matrix>): Convert Distance to Similarity for Matrix Objects
dist_to_sim(): Convert Distance to Similarity
dist_to_sim(<nn_search>): Convert Distance to Similarity for nn_search Objects
edges(): Edges for Graph-Like Objects
edges(<neighbor_graph>): Extract edges from neighbor_graph object
estimate_sigma(): Estimate Bandwidth Parameter (Sigma) for the Heat Kernel
example_kernel_5x5(): Example 5x5 factorial kernel
expand_label_similarity(): Expand Similarity Between Labels Based on a Precomputed Similarity Matrix
factor_sim(): Compute Similarity Matrix for Factors in a Data Frame
feature_weighted_spatial_constraints(): Construct Feature-Weighted Spatial Constraints for Data Blocks
find_nn(): Find nearest neighbors
find_nn(<nnsearcher>): Find Nearest Neighbors Using nnsearcher
find_nn_among(): Find nearest neighbors among a subset
find_nn_among(<class_graph>): Find Nearest Neighbors Among Classes
find_nn_among(<nnsearcher>): Find Nearest Neighbors Among Subset Using nnsearcher
find_nn_between(): Find nearest neighbors between two sets of data points
find_nn_between(<nnsearcher>): Find Nearest Neighbors Between Two Sets Using nnsearcher
graph_weights(): Convert a Data Matrix to an Adjacency Graph
graph_weights_fast(): Fast kNN Graph Weights
heat_kernel(): Compute the Heat Kernel
helmert_contrasts(): Build Helmert orthonormal contrasts
heterogeneous_neighbors(): Heterogeneous Neighbors for class_graph Objects
homogeneous_neighbors(): Homogeneous Neighbors for class_graph Objects
inverse_heat_kernel(): inverse_heat_kernel
kernel_alignment(): Kernel alignment score
kernel_roots(): Square root and inverse square root of a PSD kernel
laplacian(): Compute Graph Laplacian of a Weight Matrix
laplacian(<neighbor_graph>): Compute Laplacian matrix for neighbor_graph object
local_global_adjacency(): Local + Global KNN Adjacency
make_doubly_stochastic(): Compute the doubly stochastic matrix from a given matrix
nclasses(): Number of Classes
nclasses(<class_graph>): Number of Classes for class_graph Objects
neighbor_graph(): Neighbor Graph
neighbor_graph(<nnsearcher>): Create Neighbor Graph from nnsearcher Object
neighbors(): Neighbors of a Set of Nodes
neighbors(<neighbor_graph>): Get neighbors for neighbor_graph object
nnsearcher(): Nearest Neighbor Searcher
node_density(): Node Density
node_density(<neighbor_graph>): Compute node density for neighbor_graph object
non_neighbors(): Get Indices of Non-neighbors of a Node
non_neighbors(<neighbor_graph>): Get non-neighbors for neighbor_graph object
normalize_adjacency(): Normalize Adjacency Matrix
normalized_heat_kernel(): normalized_heat_kernel
nvertices(): Number of Vertices in Graph-like Objects
nvertices(<neighbor_graph>): Get number of vertices in neighbor_graph object
pairwise_adjacency(): Compute a pairwise adjacency matrix for multiple graphs
print(<repulsion_graph>): Print method for repulsion_graph objects
psparse(): Apply a Function to Non-Zero Elements in a Sparse Matrix
repulsion_graph(): Create a Repulsion Graph
search_result(): Search result for nearest neighbor search
search_result(<nnsearcher>): Convert Search Results for nnsearcher Objects
spatial_adjacency(): Compute the spatial adjacency matrix for a coordinate matrix
spatial_autocor(): Compute a spatial autocorrelation matrix
spatial_constraints(): Construct a Sparse Matrix of Spatial Constraints for Data Blocks
spatial_lap_of_gauss(): Spatial Laplacian of Gaussian for coordinates
spatial_laplacian(): Compute the spatial Laplacian matrix of a coordinate matrix
spatial_smoother(): Compute the spatial smoother matrix for a coordinate matrix
sum_contrasts(): Build sum-to-zero contrasts
temporal_adjacency(): Compute the temporal adjacency matrix of a time series
temporal_autocor(): Compute the temporal autocorrelation of a matrix
temporal_laplacian(): Compute the temporal Laplacian matrix of a time series
threshold_adjacency(): Threshold Adjacency
weighted_factor_sim(): Compute Weighted Similarity Matrix for Factors in a Data Frame
weighted_knn(): Weighted k-Nearest Neighbors
weighted_spatial_adjacency(): Weighted Spatial Adjacency
within_class_neighbors(): Within-Class Neighbors
within_class_neighbors(<class_graph>): Within-Class Neighbors for class_graph Objects