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Doubly stochastic model — In statistics, a doubly stochastic model is a type of model that can arise in many contexts, but in particular in modelling time series and stochastic processes. The basic idea for a doubly stochastic model is that an observed random variable is… … Wikipedia
Stochastic modelling (insurance) — This page is concerned with the stochastic modelling as applied to the insurance industry. For other stochastic modelling applications, please see Monte Carlo method. For mathematical definition, please see Stochastic process.tochastic model… … Wikipedia
Stochastic Modeling — A method of financial modeling in which one or more variables within the model are random. Stochastic modeling is for the purpose of estimating the probability of outcomes within a forecast to predict what conditions might be like under different … Investment dictionary
stochastic — adjective Etymology: Greek stochastikos skillful in aiming, from stochazesthai to aim at, guess at, from stochos target, aim, guess more at sting Date: 1934 1. random; specifically involving a random variable < a stochastic process > 2. involving … New Collegiate Dictionary
stochastic — sto·chas·tic stə kas tik, stō adj 1) involving a random variable <a stochastic process> 2) involving chance or probability <a stochastic model of radiation induced mutation> sto·chas·ti·cal·ly ti k(ə )lē adv * * * sto·chas·tic (sto… … Medical dictionary
Stochastic volatility — models are used in the field of quantitative finance to evaluate derivative securities, such as options. The name derives from the models treatment of the underlying security s volatility as a random process, governed by state variables such as… … Wikipedia
Stochastic gradient descent — is a general optimization algorithm, but is typically used to fit the parameters of a machine learning model.In standard (or batch ) gradient descent, the true gradient is used to update the parameters of the model. The true gradient is usually… … Wikipedia
Stochastic Frontier Analysis — is a method of economic modeling. It has its starting point in the stochastic production frontier models simultaneously introduced by Aigner, Lovell and Schmidt (1977) and Meeusen and Van den Broeck (1977).The production frontier model without… … Wikipedia
Stochastic calculus — is a branch of mathematics that operates on stochastic processes. It allows a consistent theory of integration to be defined for integrals of stochastic processes with respect to stochastic processes. It is used to model systems that behave… … Wikipedia
Stochastic programming — is a framework for modeling optimization problems that involve uncertainty. Whereas deterministic optimization problems are formulated with known parameters, real world problems almost invariably include some unknown parameters. When the… … Wikipedia
Stochastic control — is a subfield of control theory which deals with the existence of uncertainty in the data. The designer assumes, in a Bayesian probability driven fashion, that a random noise with known probability distribution affects the state evolution and the … Wikipedia
