statistical linearization - definição. O que é statistical linearization. Significado, conceito
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O que (quem) é statistical linearization - definição

TRANSFORMATION OF THE LOGISTIC GROWTH CURVE IN A LINEAR MATHEMATICAL RELATIONSHIP
Hubbert Linearization
  • Example of a Hubbert Linearization on the US Lower-48 crude oil production.

Linearization         
FINDING LINEAR APPROXIMATION OF FUNCTION AT GIVEN POINT
Local linearization; Linearisation; Statespace approach to linearization; State-Space Approach; Linerization; Linearized
In mathematics, linearization is finding the linear approximation to a function at a given point. The linear approximation of a function is the first order Taylor expansion around the point of interest.
Ensemble (mathematical physics)         
  • classical]] systems in [[phase space]] (top). Each system consists of one massive particle in a one-dimensional [[potential well]] (red curve, lower figure). The initially compact ensemble becomes swirled up over time.
  • Visual representation of five statistical ensembles (from left to right): [[microcanonical ensemble]], [[canonical ensemble]], [[grand canonical ensemble]], [[isobaric-isothermal ensemble]], [[isoenthalpic-isobaric ensemble]]
SET OF POSSIBLE STATES
Using statistical ensembles; Using Statistical Ensembles; Ensemble average; Statistical ensemble; Thermodynamic ensemble; Gibbsian ensemble; Statistical Ensemble; Ensemble averaging (statistical mechanics); Ensemble average (statistical mechanics); Statistical ensemble (mathematical physics)
In physics, specifically statistical mechanics, an ensemble (also statistical ensemble) is an idealization consisting of a large number of virtual copies (sometimes infinitely many) of a system, considered all at once, each of which represents a possible state that the real system might be in. In other words, a statistical ensemble is a set of systems of particles used in statistical mechanics to describe a single
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:

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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.