6.12. Matching¶

Q-1:

Barabási-Albert Model
Algorithm for generating random scale-free 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.
Heavy-tailed 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.
Scale-Free 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.