niestacjonarnej

Niestacjonarnej is the feminine singular form of the Polish adjective niestacjonarny, used to describe non-stationary phenomena in statistics, econometrics and signal processing. It characterizes processes, time series or signals whose statistical properties do not remain constant over time.

A non-stationary process is one in which key characteristics such as the mean, variance or autocovariance depend on time. Common sources of non-stationarity include a deterministic or stochastic trend, seasonality, structural breaks, changing volatility, and unit roots. Identifying non-stationarity is important because it affects modeling choices and the validity of statistical inferences.

Detection and handling typically involve specialized tests and transformations. Tests such as the Augmented Dickey-Fuller (ADF) test, KPSS test and others are used to assess stationarity. When non-stationarity is present, analysts often difference the series, remove trends or seasonality, or apply transformations to achieve stationarity. Models designed for non-stationary data include certain forms of ARIMA and fractionally integrated models, and concepts like cointegration allow for meaningful modeling of multiple non-stationary series.

Examples of niestacjonarnej phenomena appear in many domains, including economics, climatology and engineering. In practice, data observed in levels may be non-stationary, while increments or log-returns can be stationary, guiding model choice and forecasting strategy.

Etymology: the term derives from the prefix nie- (negation) and the adjective stacjonarny (stationary). The form niestacjonarnej is used in phrases such as "serii czasowej niestacjonarnej" to agree with feminine nouns in the genitive.