Stationarity: meaning, definitions and examples
⏳
stationarity
[ ˌsteɪʃəˈnerɪti ]
time series analysis
Stationarity is a property of a time series where the statistical properties such as mean, variance, and autocorrelation are constant over time.
Synonyms
Examples of usage
- The stationarity of a time series is important for accurate forecasting.
- Detecting non-stationarity in a time series can help in identifying trends or seasonal patterns.
Translations
Translations of the word "stationarity" in other languages:
🇵🇹 estacionariedade
🇮🇳 स्थिरता
🇩🇪 Stationarität
🇮🇩 stasioneritas
🇺🇦 стаціонарність
🇵🇱 stacjonarność
🇯🇵 定常性 (ていじょうせい)
🇫🇷 stationnarité
🇪🇸 estacionariedad
🇹🇷 durağanlık
🇰🇷 정상성 (jeongsangseong)
🇸🇦 الاستقرارية
🇨🇿 stacionarita
🇸🇰 stacionarita
🇨🇳 平稳性 (píngwěn xìng)
🇸🇮 stacionarnost
🇮🇸 stöðugleiki
🇰🇿 стационарлық
🇬🇪 სტაციონარულობა
🇦🇿 stasionarlıq
🇲🇽 estacionariedad
Word origin
The concept of stationarity in time series analysis dates back to the early 20th century when statisticians started exploring the behavior of data over time. It plays a crucial role in forecasting and modeling various phenomena, from stock prices to weather patterns.