Point processes are mathematical objects that are defined on some underlying mathematical space. Since these processes are often used to represent collections of points randomly scattered in physical space, time or both, the underlying space is usually d-dimensional Euclidean space denoted here by, but they can be defined on more abstract mathematical spaces. Point processes have a number of interpretations, which is reflected by the various types of point process notation. For example, if a point belongs to or is a member of a point process, denoted by, then this can be written as: and represents the point process being interpreted as a random set. Alternatively, the number of points of located in some Borel set is often written as: which reflects a random measure interpretation for point processes. These two notations are often used in parallel or interchangeably.
For some integer, the -th power of a point process is defined as: where is a collection of not necessarily disjoint Borel sets, which form a -fold Cartesian product of sets denoted by. The symbol denotes standard multiplication. The notation reflects the interpretation of the point process as a random measure. The -th power of a point process can be equivalently defined as: where summation is performed over all -tuples of points, and denotes an indicator function such that is a Dirac measure. This definition can be contrasted with the definition of the n-factorial power of a point process for which each n-tuples consists of n points.
''n''-th moment measure
The -th moment measure is defined as: where the E denotes the expectation of the point process. In other words, the n-th moment measure is the expectation of the n-th power of some point process. The th moment measure of a point process is equivalently defined as: where is any non-negativemeasurable function on and the sum is over -tuples of points for which repetition is allowed.
For some Borel set B, the first moment of a point process N is: where is known, among other terms, as the intensity measure or mean measure, and is interpreted as the expected or average number of points of found or located in the set.
The second moment measure for two Borel sets and is: which for a single Borel set becomes where denotes the variance of the random variable. The previous variance term alludes to how moments measures, like moments of random variables, can be used to calculate quantities like the variance of point processes. A further example is the covariance of a point process for two Borel sets and, which is given by:
For a general Poisson point process with intensity measure the first moment measure is: which for a homogeneous Poisson point process with constant intensity means: where is the length, area or volume of. For the Poisson case with measure the second moment measure defined on the product set is: which in the homogeneous case reduces to