statistics, a stationary process (or a strict/strictly stationary process or strong/strongly stationary process) is a stochastic process whose unconditional...

trend-stationary process is a stochastic process from which an underlying trend (function solely of time) can be removed, leaving a stationary process. The...

stationary ergodic process is a stochastic process which exhibits both stationarity and ergodicity. In essence this implies that the random process will...

time series to be non-stationary, yet have no unit root and be trend-stationary. In both unit root and trend-stationary processes, the mean can be growing...

distribution of a stationary process or stationary time series The set of joint probability distributions of a stationary process or stationary time series...

stochastic process. For a strongly stationary process, the conditional entropy for latest random variable eventually tend towards this rate value. A process X...

time. If { X t } {\displaystyle \left\{X_{t}\right\}} is a weakly stationary (WSS) process, then the following are true:: p. 163  μ t 1 = μ t 2 ≜ μ {\displaystyle...

states; every stationary process in N outcomes is a Bernoulli scheme, and vice versa. Bessel process Birth–death process Branching process Branching random...

Unit root processes, trend-stationary processes, autoregressive processes, and moving average processes are specific forms of processes with autocorrelation...

proportion of time which the server is occupied. The probability that the stationary process is in state i (contains i customers, including those in service) is: 172–173 ...

The term "stationary source" may refer to one of the following: A source of data produced by a stationary process, in the mathematical theory of probability...

[-\log c(n,n,X)]} exist and are equal for any stationary process including the stationary ergodic process X. Denote it as H. Argue that both c ( i , k...

generally converge if the sample sequence comes from sampling almost any stationary process, in which case the sample sequence is not square summable, and is...

distribution of the stationary stochastic process remains the same. A sequence of random variables forms a stationary stochastic process only if the random...

covariance-stationary series. A time series is integrated of order d if ( 1 − L ) d X t   {\displaystyle (1-L)^{d}X_{t}\ } is a stationary process, where...

n-fBm. n-fBm is a Gaussian, self-similar, non-stationary process whose increments of order n are stationary. For n = 1, n-fBm is classical fBm. Like the...

various statistics of a stochastic process. For example, a wide-sense stationary process X ( t ) {\displaystyle X(t)} has constant mean μ X = E [ X ( t ) ]...

interleaved stationary processes. For example, the maximum daily temperature in New York City can be modeled as a cyclostationary process: the maximum...

In probability theory, a stochastic process is said to have stationary increments if its change only depends on the time span of observation, but not on...

Mathematically, random vibration is characterized as an ergodic and stationary process. A measurement of the acceleration spectral density (ASD) is the usual...

the Poisson process located in some region of space. The resulting point process is called a homogeneous or stationary Poisson point process. In the second...

process the two concepts are equivalent.: p. 518  A Gaussian stochastic process is strict-sense stationary if and only if it is wide-sense stationary...

hold the stationary phase in place. The separation process in CPC is governed solely by the partitioning of solutes between the stationary and mobile...

function of a wide-sense-stationary random process has a spectral decomposition given by the power spectral density of that process. Norbert Wiener proved...

and short-range dependent stationary process is in terms of their autocovariance functions. For a short-range dependent process, the coupling between values...

time series to be non-stationary, have no unit root yet be trend-stationary. In both unit root and trend-stationary processes, the mean can be growing...

time-reversed process is defined to be X ^ t = X T − t {\displaystyle {\hat {X}}_{t}=X_{T-t}} . By Kelly's lemma this process has the same stationary distribution...

and random processes. Academic Press. pp. 370–5. The Wiener–Khinchin theorem makes sense of this formula for any wide-sense stationary process under weaker...

software Static analysis Stationary distribution Stationary ergodic process Stationary process Stationary sequence Stationary subspace analysis Statistic...

frequently are non-stationary. They are typically modelled as either trend-stationary or difference stationary. A trend stationary process {yt} evolves according...