Degenerate distribution

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A probability distribution with all mass concentrated at a single point


Degenerate distribution[edit | edit source]

A degenerate distribution is a probability distribution in which all the probability mass is concentrated at a single point. This means that the random variable associated with this distribution is almost surely equal to a constant value. In other words, the outcome is deterministic.

Illustration of a degenerate distribution

Definition[edit | edit source]

Formally, a degenerate distribution is defined for a random variable \(X\) such that:

\[ P(X = x_0) = 1 \]

for some constant \(x_0\). This implies that for any other value \(x \neq x_0\), the probability is zero:

\[ P(X = x) = 0 \]

Properties[edit | edit source]

  • Mean: The mean of a degenerate distribution is the constant value \(x_0\) at which all the probability mass is concentrated.
  • Variance: The variance of a degenerate distribution is zero, as there is no variability in the outcomes.
  • Support: The support of a degenerate distribution is the singleton set \(\{x_0\}\).

Examples[edit | edit source]

  • A coin that always lands on heads is an example of a degenerate distribution, where the outcome is always "heads".
  • A die that always rolls a six is another example, with the outcome always being the number six.

Applications[edit | edit source]

Degenerate distributions are often used in probability theory and statistics to model deterministic processes. They are also used in stochastic processes as a limiting case where randomness is absent.

Related concepts[edit | edit source]

  • Dirac measure: A measure that assigns all mass to a single point, similar to a degenerate distribution.
  • Deterministic system: A system in which no randomness is involved in the development of future states.

Related pages[edit | edit source]

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