Roloffset

Roloffset is a term used in the context of rolling computations and time-series processing to describe the alignment offset between a computed rolling statistic and the original data series. It represents where the result of a rolling operation is anchored in time relative to the input window.

Formally, suppose a data series x_t is processed with a rolling function F over a window of width w, producing a statistic R_t = F(x_{t−w+1}, ..., x_t). The roloffset r specifies the time index to which R_t is associated. If r = 0, the result is associated with the right endpoint t; if r > 0, the result is shifted forward in time, and if r < 0, the result is shifted backward. Common variants include right-aligned (r = 0), centered (approximately r ≈ (w−1)/2 for odd w), and left-aligned (r = w−1).

Applications of roloffset appear in time-series analysis, signal processing, and data pipelines where downstream steps rely on precise temporal alignment between inputs and computed statistics. For example, a rolling mean with a window of three samples can be anchored to the most recent sample (right-aligned) or to the window’s center (centered), affecting how the result is synchronized with timestamps.

Implementation notes include handling of boundary conditions where there are fewer than w observations, often resulting in NaNs or padding. In software libraries, roloffset is commonly exposed as an alignment or offset parameter, sometimes under different names such as align, center, or lag; the exact behavior depends on the specific library’s conventions.

While roloffset is a descriptive concept in rolling window computations, it is not universally standardized as a single, formal term across all domains.

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