Suppose I have a sample (S) of a graph where S is a subset of G -- the population Graph. Is there a way (theoretical) to compute for bias in the estimation of centralization (as in igraph::centr_degree(g)$centralization) AND use this computed bias to correct my estimate?
Additional info: Suppose I used bootstrap graph samples (i.e. S*1,S*2, . . . ,S*n) and I know from my histogram of centralization from these samples that I am "far" from the population centralization. For illustration, a histogram of centralization is found below. Unfortunately, the population centralization is 0.011.