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En esta página puede obtener un análisis detallado de una palabra o frase, producido utilizando la mejor tecnología de inteligencia artificial hasta la fecha:
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- etimología
Qué (quién) es stochastic linearization - definición
TRANSFORMATION OF THE LOGISTIC GROWTH CURVE IN A LINEAR MATHEMATICAL RELATIONSHIP
Hubbert Linearization
![Norway]]'s oil production](https://commons.wikimedia.org/wiki/Special:FilePath/HubbertLin_Norway.svg?width=200 "Norway]]'s oil production")
![Norway]]'s oil production](https://commons.wikimedia.org/wiki/Special:FilePath/Hubbert_Norway.svg?width=200 "Norway]]'s oil production")
Stochastic optimization
Stochastic search; Stochastic optimisation
Stochastic optimization (SO) methods are optimization methods that generate and use random variables. For stochastic problems, the random variables appear in the formulation of the optimization problem itself, which involves random objective functions or random constraints.
Stochastic modelling (insurance)
PROBABILITY MODELLING TOOL
Stochastic modeling; Stochastic modelling
"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.
Stochastic 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"/>](https://commons.wikimedia.org/wiki/Special:FilePath/BMonSphere.jpg?width=200 "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\"/>")
![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"/>](https://commons.wikimedia.org/wiki/Special:FilePath/Joseph Doob.jpg?width=200 "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\"/>")
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)
In probability theory and related fields, a stochastic () or random process is a mathematical object usually defined as a family of random variables. Stochastic processes are widely used as mathematical models of systems and phenomena that appear to vary in a random manner.
Wikipedia
Hubbert linearization
The Hubbert linearization is a way to plot production data to estimate two important parameters of a Hubbert curve, the approximated production rate of a nonrenewable resource following a logistic distribution:
- the logistic growth rate and
- the quantity of the resource that will be ultimately recovered.
The linearization technique was introduced by Marion King Hubbert in his 1982 review paper. The Hubbert curve is the first derivative of a logistic function, which has been used for modeling the depletion of crude oil in particular, the depletion of finite mineral resources in general and also population growth patterns.
