> ## Documentation Index
> Fetch the complete documentation index at: https://nixtla-old-docs.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.
> Built-in lag transformations
# Lag transforms
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### RollingQuantile
> ```text theme={null}
> RollingQuantile (p:float, window_size:int,
> min_samples:Optional[int]=None)
> ```
*Rolling statistic*
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### RollingMax
> ```text theme={null}
> RollingMax (window_size:int, min_samples:Optional[int]=None)
> ```
*Rolling statistic*
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### RollingMin
> ```text theme={null}
> RollingMin (window_size:int, min_samples:Optional[int]=None)
> ```
*Rolling statistic*
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### RollingStd
> ```text theme={null}
> RollingStd (window_size:int, min_samples:Optional[int]=None)
> ```
*Rolling statistic*
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### RollingMean
> ```text theme={null}
> RollingMean (window_size:int, min_samples:Optional[int]=None)
> ```
*Rolling statistic*
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### SeasonalRollingQuantile
> ```text theme={null}
> SeasonalRollingQuantile (p:float, season_length:int, window_size:int,
> min_samples:Optional[int]=None)
> ```
*Rolling statistic over seasonal periods*
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### SeasonalRollingMax
> ```text theme={null}
> SeasonalRollingMax (season_length:int, window_size:int,
> min_samples:Optional[int]=None)
> ```
*Rolling statistic over seasonal periods*
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### SeasonalRollingMin
> ```text theme={null}
> SeasonalRollingMin (season_length:int, window_size:int,
> min_samples:Optional[int]=None)
> ```
*Rolling statistic over seasonal periods*
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### SeasonalRollingStd
> ```text theme={null}
> SeasonalRollingStd (season_length:int, window_size:int,
> min_samples:Optional[int]=None)
> ```
*Rolling statistic over seasonal periods*
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### SeasonalRollingMean
> ```text theme={null}
> SeasonalRollingMean (season_length:int, window_size:int,
> min_samples:Optional[int]=None)
> ```
*Rolling statistic over seasonal periods*
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### ExpandingQuantile
> ```text theme={null}
> ExpandingQuantile (p:float)
> ```
*Expanding statistic*
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### ExpandingMax
> ```text theme={null}
> ExpandingMax ()
> ```
*Expanding statistic*
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### ExpandingMin
> ```text theme={null}
> ExpandingMin ()
> ```
*Expanding statistic*
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### ExpandingStd
> ```text theme={null}
> ExpandingStd ()
> ```
*Expanding statistic*
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### ExpandingMean
> ```text theme={null}
> ExpandingMean ()
> ```
*Expanding statistic*
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### ExponentiallyWeightedMean
> ```text theme={null}
> ExponentiallyWeightedMean (alpha:float)
> ```
*Exponentially weighted average*
| | **Type** | **Details** |
| ----- | -------- | ----------------- |
| alpha | float | Smoothing factor. |
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### Offset
> ```text theme={null}
> Offset (tfm:__main__._BaseLagTransform, n:int)
> ```
*Shift series before computing transformation*
| | **Type** | **Details** |
| --- | ------------------ | ---------------------------------------------------------------------------- |
| tfm | \_BaseLagTransform | Transformation to be applied |
| n | int | Number of positions to shift (lag) series before applying the transformation |
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### Combine
> ```text theme={null}
> Combine (tfm1:__main__._BaseLagTransform,
> tfm2:__main__._BaseLagTransform, operator:Callable)
> ```
*Combine two lag transformations using an operator*
| | **Type** | **Details** |
| -------- | ------------------ | -------------------------------------------------------------------- |
| tfm1 | \_BaseLagTransform | First transformation. |
| tfm2 | \_BaseLagTransform | Second transformation. |
| operator | Callable | Binary operator that defines how to combine the two transformations. |