stochastic instability - translation to russian
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  3. stochastic instability

stochastic instability - translation to russian

PROBABILITY MODELLING TOOL
Stochastic modeling; Stochastic modelling

stochastic instability      

математика

стохастическая неустойчивость

stochastic model         
  • Wiener]] or [[Brownian motion]] process on the surface of a sphere. The Wiener process is widely considered the most studied and central stochastic process in probability theory.<ref name="doob1953stochasticP46to47"/><ref name="RogersWilliams2000page1"/><ref name="Steele2012page29"/>
  • red}}).
  • Mathematician [[Joseph Doob]] did early work on the theory of stochastic processes, making fundamental contributions, particularly in the theory of martingales.<ref name="Getoor2009"/><ref name="Snell2005"/> His book ''Stochastic Processes'' is considered highly influential in the field of probability theory.<ref name="Bingham2005"/>
  • [[Norbert Wiener]] gave the first mathematical proof of the existence of the Wiener process. This mathematical object had appeared previously in the work of [[Thorvald Thiele]], [[Louis Bachelier]], and [[Albert Einstein]].<ref name="JarrowProtter2004"/>
  • A single computer-simulated '''sample function''' or '''realization''', among other terms, of a three-dimensional Wiener or Brownian motion process for time 0 ≤ t ≤ 2. The index set of this stochastic process is the non-negative numbers, while its state space is three-dimensional Euclidean space.
MATHEMATICAL OBJECT USUALLY DEFINED AS A COLLECTION OF RANDOM VARIABLES
Random function; Theory of random functions; Stochastic processes; Random process; Stochastic transition function; Heterogeneous process; Stochastic effects; Stochastic Process; Random signal; Random system; Random processes; Stochastic model; Stochastic systems; Homogeneous process; Stochastic models; Kolmogorov extension; Stochastic system; Process (stochastic); Discrete-time stochastic process; Stochastic dynamics; Stochastic deaths; Stochastic processe; Stochastic Processes; Real-valued stochastic process; Version (probability theory)

общая лексика

вероятностная модель

homogeneous process         
  • Wiener]] or [[Brownian motion]] process on the surface of a sphere. The Wiener process is widely considered the most studied and central stochastic process in probability theory.<ref name="doob1953stochasticP46to47"/><ref name="RogersWilliams2000page1"/><ref name="Steele2012page29"/>
  • red}}).
  • Mathematician [[Joseph Doob]] did early work on the theory of stochastic processes, making fundamental contributions, particularly in the theory of martingales.<ref name="Getoor2009"/><ref name="Snell2005"/> His book ''Stochastic Processes'' is considered highly influential in the field of probability theory.<ref name="Bingham2005"/>
  • [[Norbert Wiener]] gave the first mathematical proof of the existence of the Wiener process. This mathematical object had appeared previously in the work of [[Thorvald Thiele]], [[Louis Bachelier]], and [[Albert Einstein]].<ref name="JarrowProtter2004"/>
  • A single computer-simulated '''sample function''' or '''realization''', among other terms, of a three-dimensional Wiener or Brownian motion process for time 0 ≤ t ≤ 2. The index set of this stochastic process is the non-negative numbers, while its state space is three-dimensional Euclidean space.
MATHEMATICAL OBJECT USUALLY DEFINED AS A COLLECTION OF RANDOM VARIABLES
Random function; Theory of random functions; Stochastic processes; Random process; Stochastic transition function; Heterogeneous process; Stochastic effects; Stochastic Process; Random signal; Random system; Random processes; Stochastic model; Stochastic systems; Homogeneous process; Stochastic models; Kolmogorov extension; Stochastic system; Process (stochastic); Discrete-time stochastic process; Stochastic dynamics; Stochastic deaths; Stochastic processe; Stochastic Processes; Real-valued stochastic process; Version (probability theory)

математика

однородный процесс

Definition

stochastic

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 and Stochastic asset models. For mathematical definition, please see Stochastic process.

"Stochastic" means being or having a random variable. A stochastic model is a tool for estimating probability distributions of potential outcomes by allowing for random variation in one or more inputs over time. The random variation is usually based on fluctuations observed in historical data for a selected period using standard time-series techniques. Distributions of potential outcomes are derived from a large number of simulations (stochastic projections) which reflect the random variation in the input(s).

Its application initially started in physics. It is now being applied in engineering, life sciences, social sciences, and finance. See also Economic capital.

https://en.wikipedia.org/wiki/Stochastic modelling (insurance)
What is the Russian for stochastic instability? Translation of &#39stochastic instability&#39 to Rus
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