Computes variance of Y at ego level

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Description

Computes variance of Y at ego level

Usage

1
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).

Details

For each vertex i the variance is computed as follows

(sum_j a(ij))^(-1) * ∑_j a(ij) * [f(y(i),y(j)) - f(i)]^2

Where a(ij) is the ij-th element of graph, f is the function specified in funname, and, if all=FALSE f(i)=∑_j a(ij)f(y(i), y(j))^2/∑_j a(ij), otherwise f(i)=f(j)=(1/n^2)∑_(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.

Value

A numeric vector of length n.

See Also

struct_test

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

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