
Hi All,

My question is more academic than technical.

The question is about interpretation of Poisson curve. I am using it to assess scale-free nature of degree distribution. Can you please briefly describe what is meant by the Poisson curve when you give it your range of k-neighbour data which apparently follows power-law (or does otherwise). The code I am using within the xyplot.panel to plot the Poisson curve follows. y is the degrees vector.

        kfreq <- table(y); # compute frequency hash table of y, the degrees
        k <- 1:max(y)
        for (i in k) {
            ichar <- as.character(i) # convert to match the names(freq), the character-based hash key of freq, which is degree-value
            if (!(ichar %in% names(kfreq)))
                kfreq[ichar] <- 0
        }
        sortedkeys <- as.character(k)
        kfreq <-  kfreq[sortedkeys]
        pk <- kfreq / length(y)
        panel.xyplot(col="blue", k, pk)

        #overlaying the poisson distribution
        poissonk <- ppois(k, lambda = mean(y), lower.tail = FALSE) # lower.tail: if TRUE (default), probabilities are P[X <= x], otherwise, P[X > x]
        panel.xyplot(col="red", k, poissonk)

Regrads,
Fayez
GCA lab - UIUC

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