R: Constructing Adjacency Matrices Based on Spatial and Feature Similarity

# Constructing Adjacency Matrices Based on Spatial and Feature Similarity

## Documentation for package ‘adjoin’ version 0.1.0

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package NEWS
- Package README

## Help Pages

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 | Convert Distance to Similarity
dist_to_sim.Matrix | Convert Distance to Similarity for Matrix Objects
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
neighbors | Neighbors of a Set of Nodes
neighbors.neighbor_graph | Get neighbors for neighbor_graph object
neighbor_graph | Neighbor Graph
neighbor_graph.igraph | Neighbor Graph
neighbor_graph.Matrix | Neighbor Graph
neighbor_graph.matrix | Neighbor Graph
neighbor_graph.nnsearcher | Create Neighbor Graph from nnsearcher 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
normalized_heat_kernel | normalized_heat_kernel
normalize_adjacency | Normalize Adjacency Matrix
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_laplacian | Compute the spatial Laplacian matrix of a coordinate matrix
spatial_lap_of_gauss | Spatial Laplacian of Gaussian for coordinates
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