ego_variance function

Computes variance of $Y$ at ego level

ego_variance(graph, Y, funname, all = FALSE)

Arguments

• graph: A matrix of size $n*n$ of class dgCMatrix.
• Y: A numeric vector of length $n$.
• funname: Character scalar. Comparison to make (see vertex_covariate_compare).
• all: Logical scalar. When FALSE (default) $f_i$ is mean at ego level. Otherwise is fix for all i (see details).

Returns

A numeric vector of length $n$.

Details

For each vertex $i$ the variance is computed as follows

Where $a(ij)$ is the ij-th element of graph, $f$ is the function specified in funname, and, if all=FALSE

$f(i)=\sum_j a(ij)f(y(i), y(j))^2/\sum_j a(ij)$, otherwise $f(i)=f(j)=(1/n^2)\sum_(i,j) f(y_i,y_j)$

This is an auxiliary function for struct_test. The idea is to compute an adjusted measure of disimilarity between vertices, so the closest in terms of $f$ is $i$ to its neighbors, the smaller the relative variance.

See Also

struct_test

Other statistics: bass, classify_adopters(), cumulative_adopt_count(), dgr(), exposure(), hazard_rate(), infection(), moran(), struct_equiv(), threshold(), vertex_covariate_dist()