This article does not cite any sources. Please help improve this article by adding citations to reliable sources. Unsourced material may be challenged and removed.Find sources: "Singular distribution" – news · newspapers · books · scholar · JSTOR (March 2024) (Learn how and when to remove this message)

In probability, a **singular distribution** is a probability distribution concentrated on a set of Lebesgue measure zero, where the probability of each point in that set is zero.

These distributions are sometimes called **singular continuous distributions**, since their cumulative distribution functions are singular and continuous.

Such distributions are not absolutely continuous with respect to Lebesgue measure.

A singular distribution is not a discrete probability distribution because each discrete point has a zero probability. On the other hand, neither does it have a probability density function, since the Lebesgue integral of any such function would be zero.

In general, distributions can be described as a discrete distribution (with a probability mass function), an absolutely continuous distribution (with a probability density), a singular distribution (with neither), or can be decomposed into a mixture of these.

An example is the Cantor distribution; its cumulative distribution function is a devil's staircase. Less curious examples appear in higher dimensions. For example, the upper and lower Fréchet–Hoeffding bounds are singular distributions in two dimensions.