Search results
Results from the WOW.Com Content Network
Instead of dealing with only one possible reality of how the process might evolve over time (as is the case, for example, for solutions of an ordinary differential equation), in a stochastic or random process there is some indeterminacy in its future evolution described by probability distributions. This means that even if the initial condition ...
In stochastic analysis, a part of the mathematical theory of probability, a predictable process is a stochastic process whose value is knowable at a prior time. The predictable processes form the smallest class that is closed under taking limits of sequences and contains all adapted left-continuous processes. [clarification needed]
Structural determinism is the philosophical view that actions, events, and processes are predicated on and determined by structural factors. [35] Given any particular structure or set of estimable components, it is a concept that emphasizes rational and predictable outcomes.
Hindsight bias, also known as the knew-it-all-along phenomenon [1] or creeping determinism, [2] is the common tendency for people to perceive past events as having been more predictable than they were.
In stochastic analysis a random process is a predictable process if it is possible to know the next state from the present time. The branch of mathematics known as Chaos Theory focuses on the behavior of systems that are highly sensitive to initial conditions. It suggests that a small change in an initial condition can completely alter the ...
The concept of allostasis, maintaining stability through change, is a fundamental process through which organisms actively adjust to both predictable and unpredictable events... Allostatic load refers to the cumulative cost to the body of allostasis, with allostatic overload... being a state in which serious pathophysiology can occur...
In other words, the deterministic nature of these systems does not make them predictable. [11] [12] This behavior is known as deterministic chaos, or simply chaos. The theory was summarized by Edward Lorenz as: [13] Chaos: When the present determines the future but the approximate present does not approximately determine the future.
In information theory and statistics, negentropy is used as a measure of distance to normality. [4] [5] [6] Out of all distributions with a given mean and variance, the normal or Gaussian distribution is the one with the highest entropy.