In probability theory, a continuous stochastic process is a type of stochastic process that may be said to be "continuous" as a function of its "time"...

In probability theory and related fields, a stochastic (/stəˈkæstɪk/) or random process is a mathematical object usually defined as a family of random...

theory and statistics, a continuous-time stochastic process, or a continuous-space-time stochastic process is a stochastic process for which the index variable...

Branching process Branching random walk Brownian bridge Brownian motion Chinese restaurant process CIR process Continuous stochastic process Cox process Dirichlet...

A continuous-time Markov chain (CTMC) is a continuous stochastic process in which, for each state, the process will change state according to an exponential...

diffusion processes are a class of continuous-time Markov process with almost surely continuous sample paths. Diffusion process is stochastic in nature...

calculus to stochastic processes such as Brownian motion (see Wiener process). It has important applications in mathematical finance and stochastic differential...

In mathematics, a sample-continuous process is a stochastic process whose sample paths are almost surely continuous functions. Let (Ω, Σ, P) be a probability...

process (or Brownian motion, due to its historical connection with the physical process of the same name) is a real-valued continuous-time stochastic...

mathematics, a Feller-continuous process is a continuous-time stochastic process for which the expected value of suitable statistics of the process at a given time...

Markov decision process (MDP), also called a stochastic dynamic program or stochastic control problem, is a model for sequential decision making when...

A stochastic differential equation (SDE) is a differential equation in which one or more of the terms is a stochastic process, resulting in a solution...

summarizes the dynamics of a continuous stochastic process. It is used to define a probability density for a stochastic process, and it is similar to the...

probability theory and statistics, a Markov chain or Markov process is a stochastic process describing a sequence of possible events in which the probability...

In probability theory and statistics, a Gaussian process is a stochastic process (a collection of random variables indexed by time or space), such that...

In stochastic analysis, a part of the mathematical theory of probability, a predictable process is a stochastic process whose value is knowable at a prior...

a stationary process (also called a strict/strictly stationary process or strong/strongly stationary process) is a stochastic process whose statistical...

the conic sections and related shapes In probability theory Continuous stochastic process Continuity equations applicable to conservation of mass, energy...

process, also called the Brownian motion process. One of the simplest continuous-time stochastic processes is Brownian motion. This was first observed...

In mathematics, the Ornstein–Uhlenbeck process is a stochastic process with applications in financial mathematics and the physical sciences. Its original...

Galton–Watson process, also called the Bienaymé-Galton-Watson process or the Galton-Watson branching process, is a branching stochastic process arising from...

In probability theory, a Lévy process, named after the French mathematician Paul Lévy, is a stochastic process with independent, stationary increments:...

Fokker–Planck equation, and never used again. In general, continuous stochastic processes are essentially Markovian, and so Fokker–Planck equations are...

Brownian motion, continuous stochastic process where the logarithm of a variable follows a Brownian movement, that is a Wiener process Gradient boosting...

P(t=0)=\alpha } . Continuous-time stochastic process Continuous function Continuous geometry Continuous modelling Continuous or discrete spectrum Continuous spectrum...

function Continuous function (set theory) Continuous stochastic process Normal function Open and closed maps Piecewise Symmetrically continuous function...

A jump process is a type of stochastic process that has discrete movements, called jumps, with random arrival times, rather than continuous movement, typically...

The context may be either discrete time or continuous time. An extremely well-studied formulation in stochastic control is that of linear quadratic Gaussian...

A stochastic simulation is a simulation of a system that has variables that can change stochastically (randomly) with individual probabilities. Realizations...

In statistics, stochastic volatility models are those in which the variance of a stochastic process is itself randomly distributed. They are used in the...