Sentence examples for matrix of network from inspiring English sources

Note that our matrix of network proximity takes into account all pairs of traded corporations.

This corresponds with w y (G,Y) in Eq. 16 above being defined as w y (G,Y =ω, where ω is the matrix of network statistics of interest, and w x (G,X) being defined as ι.

The above process could be denoted as xt + 1 = Px t, where P represents the matrix of transition probability, which is column-normalized matrix of weighted adjacency matrix of network graph G.

The shape of the function (boldsymbol {f}_{bar {boldsymbol {y}}} and the choice of statistics in (bar {boldsymbol {w}}_{bar {boldsymbol {y}}}(boldsymbol {G})=bar {boldsymbol {omega }}), where (bar {boldsymbol {omega }}) is an ((Mtimes bar {R})) matrix of network statistics, are again, ideally, motivated by theory.

Given an unweighted and undirected network G = ( V, E ), suppose the vertices are divided into communities such that vertex i belongs to community r ( i ) denoted by c r ( i ) ; the function Q is defined as Equation (7), where A = ( A i j ) n × n is the adjacency matrix of network G.

For each year, we define a matrix of network proximity D of size N × N, where N is the number of observed traded corporations in a year, D i j = 1 / ( d i j ), and d i j is the degree of separation (number of links) between corporation i and j in the interlocking network.

These new matrices are generated by bootstrapping elements with replacement from the original matrices of network proximity.

Finally, for each year, we measure the correlation between the newly generated matrices of network proximity and market similarity.

Spearman partial Mantel correlations (Pearson correlations yield similar results) between the matrices of network proximity and market similarity of traded corporations in each year.

Moreover, to recover the transfer matrices of network coding at the destination node, a coefficient vector of k symbols is usually included in each of the transmitted packets [3].

We calculate partial Mantel correlations [24] (both Spearman and Pearson correlations) between the matrices of network proximity and market similarity while controlling for other proximity matrices given by market sector, geographic distance, board size, fraction of directors with financial expertise, and average stock price in the year (see the Appendix for further details).