Stationary Process | Mathematics, Stochastic Process, Joint Probability Pistribution, Time Series, Cyclostationary Process, Law of Large Numbers, Cumulative Distribution Function

Publisher

OmniScriptum

Publication Date

2026

Language

English

ISBN 10

6130330995

ISBN 13

9786130330996

Binding

Taschenbuch

Condition

Neu

Dimensions

Weight

131 grams

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Synopsis

Please note that the content of this book primarily consists of articles available from Wikipedia or other free sources online. In the mathematical sciences, a stationary process (or strict(ly) stationary process or strong(ly) stationary process) is a stochastic process whose joint probability distribution does not change when shifted in time or space. As a result, parameters such as the mean and variance, if they exist, also do not change over time or position. Stationarity is used as a tool in time series analysis, where the raw data are often transformed to become stationary, for example, economic data are often seasonal and/or dependent on the price level. Processes are described as trend stationary if they are a linear combination of a stationary process and one or more processes exhibiting a trend. Transforming these data to leave a stationary data set for analysis is referred to as de-trending.

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