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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