6.12. Matching¶

Q1:
 BarabásiAlbert Model
 Algorithm for generating random scalefree networks using a preferential attachment mechanism.
 WS Model
 Has characteristics of a small world network, like the data, but it has low variability in the number of neighbors from node to node, unlike the data.
 Probability Mass Function (PmF)
 A function that maps from each value to it's probabilities.
 Growth
 Instead of starting with a fixed number of vertices, the BA model starts with a small graph and adds vertices one at a time.
 Heavytailed Distributions
 A probability theory with probability distributions whose tails are not exponentially bounded.
 Standard Deviation
 Used to indicate the extent of deviation for a group as a whole.
 Power Law
 A distribution follows this law if :math:`PMF(k) ∼ k−α` where ``PMF(k)`` is the fraction of nodes with degree ``k``, ``α`` is a parameter, and the symbol ∼ indicates that the ``PMF`` is asymptotic to ``k−α`` as ``k`` increases.
 Preferential Attachment
 A quantity of something is distributed according to how much already exsisting recipients have.
 ScaleFree Network
 A network whose degree distribution follows a power law, at least asymptotically.
 Cumulative Distribution Function
 Maps a value to the fraction of values less thank or equal to x.
 Complementary CDF
 :math:`CCDF(x) ≡ 1  CDF(x)`
 Explanatory Models
 A model that gives a useful description of why and how a phenomenon is the way it is.
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