- 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.
- 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.
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