LinearAlgebra

Wiki ▸ API Reference ▸ Statistics/Linear Algebra

• reorder.fiedler_vector - compute the Fiedler vector of a graph: the eigenvector with the smallest non-null eigenvalue of the Laplacian of the graph.
• reorder.correlation - compute the Pearson correlation of two rows.
• reorder.covariance - compute the covariance of two rows.
• reorder.covariancetranspose - compute the covariance of two columns.
• reorder.distance - provide several distance functions.
• distance.euclidean - Euclidean (L2) distance.
• distance.manhattan - Manhattan (L1) distance.
• distance.minkowski - Minkowski distance.
• distance.chebyshev - Chebyshev distance.
• distance.hamming - Hamming distance.
• distance.jaccard - Jaccard distance.
• distance.braycurtis - Braycurtis distance.
• reorder.dist - compute pairwise distances.
• reorder.distmax - compute the maximum distance in a distance matrix.
• reorder.distmin - compute the minimum distance in a distance matrix.
• reorder.dist_remove - remove a line/column from a distance matrix.
• reorder.hcluster - hierarchical clustering.
• hcluster.linkage - get or set the type of linkage.
• hcluster.distance - get or set the distance function.
• hcluster.distanceMatrix - get or set the distance matrix.
• reorder.laplacian - compute the Laplacian of a graph.
• reorder.mean - compute the mean value of a vector.
• reorder.meancolumns - compute a column containing the means of a matrix's rows.
• reorder.meantranspose - compute the mean of a matrix column.
• reorder.poweriteration - compute the eigenvector with the largest eigenvalue from a symmetric definite positive matrix using a power iteration.
• [reorder.poweriteration_n](LinearAlgebra#poweriteration_n] - compute the n eigenvectors with the largest eivenvalues from a symmetric definite positive matrix using a power iteration.
• reorder.fix_distance_matrix - fix numerical precision issues with a computed distance matrix.
• reorder.check_distance_matrix - test if a matrix is symmetric definite positive.
• reorder.ca - compute the Correspondence Analysis (or decomposition) of a positive matrix.