Generalized Wiener process

From Wikipedia, the free encyclopedia
Jump to navigation Jump to search

In statistics, a generalized Wiener process[1] (named after Norbert Wiener) is a continuous time random walk with drift and random jumps at every point in time. Formally:

a(x,t)dt+b(x,t)ηdt

where a and b are deterministic functions, t is a continuous index for time, x is a set of exogenous variables that may change with time, dt is a differential in time, and η is a random draw from a standard normal distribution at each instant.

See also

[edit | edit source]

References

[edit | edit source]
  1. ^ Lua error in Module:Citation/CS1/Configuration at line 2172: attempt to index field '?' (a nil value).