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An additive process, in probability theory, is a cadlag, continuous in probability stochastic process with independent increments.An additive process is the generalization of a Lévy process (a Lévy process is an additive process with identically distributed increments). An example of an additive process is a Brownian motion with a time-dependent drift.The additive process is introduced by Paul Lévy in 1937. There are applications of the additive process in quantitative finance (this family of processes can capture important features of the implied volatility) and in digital image processing.

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• An additive process, in probability theory, is a cadlag, continuous in probability stochastic process with independent increments.An additive process is the generalization of a Lévy process (a Lévy process is an additive process with identically distributed increments). An example of an additive process is a Brownian motion with a time-dependent drift.The additive process is introduced by Paul Lévy in 1937. There are applications of the additive process in quantitative finance (this family of processes can capture important features of the implied volatility) and in digital image processing. (en)
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• An additive process, in probability theory, is a cadlag, continuous in probability stochastic process with independent increments.An additive process is the generalization of a Lévy process (a Lévy process is an additive process with identically distributed increments). An example of an additive process is a Brownian motion with a time-dependent drift.The additive process is introduced by Paul Lévy in 1937. There are applications of the additive process in quantitative finance (this family of processes can capture important features of the implied volatility) and in digital image processing. (en)
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