In probability theory and statistics, a stochastic order quantifies the concept of one random variable being "bigger" than another. These are usually partial...

Stochastic dominance is a partial order between random variables. It is a form of stochastic ordering. The concept arises in decision theory and decision...

spreads provides a stochastic ordering of equal-mean gambles (probability distributions) according to their degree of risk; this ordering is partial, meaning...

{\displaystyle \leq _{\mathrm {icx} }} denotes the increasing convex stochastic order defined by A ≤ i c x B {\displaystyle A\leq _{\mathrm {icx} }B} if...

I} , where ≤ s t {\displaystyle \leq _{\mathrm {st} }} denotes the stochastic order defined by A ≤ s t B {\displaystyle A\leq _{\mathrm {st} }B} if E ϕ...

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

Complete partial order Permutation, the act of arranging all the members of a set into some sequence or order Ranking Stochastic ordering of random variables...

This requires a stochastic ordering on the lotteries. Several such orderings exist; the most common in social choice theory, in order of strength, are...

Stochastic gradient descent (often abbreviated SGD) is an iterative method for optimizing an objective function with suitable smoothness properties (e...

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

1947. This article discussed alternative hypotheses, including a stochastic ordering (where the cumulative distribution functions satisfied the pointwise...

In mathematics, a stochastic matrix is a square matrix used to describe the transitions of a Markov chain. Each of its entries is a nonnegative real number...

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...

Stochastic calculus is a branch of mathematics that operates on stochastic processes. It allows a consistent theory of integration to be defined for integrals...

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

Stochastic resonance (SR) is the description of a physical phenomenon where the behavior of non-linear system where random (stochastic) fluctuations in...

mathematics, some boundary value problems can be solved using the methods of stochastic analysis. Perhaps the most celebrated example is Shizuo Kakutani's 1944...

strict/strictly stationary process or strong/strongly stationary process) is a stochastic process whose statistical properties, such as mean and variance, do not...

contained in some total order. Stochastic dominance – Partial order between random variables Strict weak ordering – strict partial order "<" in which the relation...

mathematical optimization, stochastic programming is a framework for modeling optimization problems that involve uncertainty. A stochastic program is an optimization...

t-distributed stochastic neighbor embedding (t-SNE) is a statistical method for visualizing high-dimensional data by giving each datapoint a location in...

In mathematics, specifically in the theory of Markovian stochastic processes in probability theory, the Chapman–Kolmogorov equation (CKE) is an identity...

Quantum stochastic calculus is a generalization of stochastic calculus to noncommuting variables. The tools provided by quantum stochastic calculus are...

theory, in particular, the theory of stochastic processes. He invented the concept of stochastic integral and stochastic differential equation, and is known...

an integral equation. A stochastic differential equation (SDE) is an equation in which the unknown quantity is a stochastic process and the equation...

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

flows. He is also known for the Kardar–Parisi–Zhang equation modelling stochastic aggregation. From the point of view of complex systems, he worked on the...

In economics, a random utility model (RUM), also called stochastic utility model, is a mathematical description of the preferences of a person, whose choices...

Stochastic matrix Stochastic modelling (insurance) Stochastic optimization Stochastic ordering Stochastic process Stochastic rounding Stochastic simulation Stopped...

Stochastic computing is a collection of techniques that represent continuous values by streams of random bits. Complex computations can then be computed...