Search results
Results from the WOW.Com Content Network
A process theory is a system of ideas that explains how an entity changes and develops. [1] Process theories are often contrasted with variance theories, that is, systems of ideas that explain the variance in a dependent variable based on one or more independent variables. While process theories focus on how something happens, variance theories ...
Serving as a fundamental process in queueing theory, the Poisson process is an important process for mathematical models, where it finds applications for models of events randomly occurring in certain time windows. [125] [126] Defined on the real line, the Poisson process can be interpreted as a stochastic process, [49] [127] among other random ...
In probability theory and statistics, variance is the expected value of the squared ... This difference between moment of inertia in physics and in statistics is ...
Another characterisation of a Wiener process is the definite integral (from time zero to time t) of a zero mean, unit variance, delta correlated ("white") Gaussian process. [ 4 ] The Wiener process can be constructed as the scaling limit of a random walk , or other discrete-time stochastic processes with stationary independent increments.
In probability theory and statistics, a Gaussian process is a stochastic process (a collection of random variables indexed by time or space), such that every finite collection of those random variables has a multivariate normal distribution.
In mathematics and statistics, a stationary process (also called a strict/strictly stationary process or strong/strongly stationary process) is a stochastic process whose statistical properties, such as mean and variance, do not change over time. More formally, the joint probability distribution of the process remains the same when shifted in ...
Continuous stochastic process: the question of continuity of a stochastic process is essentially a question of convergence, and many of the same concepts and relationships used above apply to the continuity question. Asymptotic distribution; Big O in probability notation; Skorokhod's representation theorem; The Tweedie convergence theorem ...
The variogram is twice the semivariogram and can be defined, differently, as the variance of the difference between field values at two locations (and , note change of notation from to and to ) across realizations of the field (Cressie 1993):