stochastic stability - перевод на русский
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stochastic stability - перевод на русский

PROBABILITY MODELLING TOOL
Stochastic modeling; Stochastic modelling
Найдено результатов: 352
stochastic stability      

математика

стохастическая устойчивость

stochastic stability      
мат.
стохастическая устойчивость
initial stability         
RESISTANCE OF A BOAT TO SMALL CHANGES IN THE DIFFERENCE BETWEEN THE VERTICAL FORCES APPLIED ON ITS TWO SIDES
Primary stability

общая лексика

начальная остойчивость

initial stability         
RESISTANCE OF A BOAT TO SMALL CHANGES IN THE DIFFERENCE BETWEEN THE VERTICAL FORCES APPLIED ON ITS TWO SIDES
Primary stability
начальная остойчивость
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

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)
вероятностная [стохастическая] модель
random 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)
случайный процесс
stochastic modeling         

математика

вероятностное (стохастическое) моделирование

stochastic optimization         
Stochastic search; Stochastic optimisation

математика

стохастическая оптимизация

Определение

stability

Википедия

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)
Как переводится stochastic stability на Русский язык
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