> ## 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.
# Expanding
# module `coreforecast.expanding`
***
## function `expanding_mean`
```python theme={null}
expanding_mean(x: ndarray) → ndarray
```
Compute the expanding\_mean of the input array.
**Args:**
* `x` (np.ndarray): Input array.
**Returns:**
* `np.ndarray`: Array with the expanding statistic
***
## function `expanding_std`
```python theme={null}
expanding_std(x: ndarray) → ndarray
```
Compute the expanding\_std of the input array.
**Args:**
* `x` (np.ndarray): Input array.
**Returns:**
* `np.ndarray`: Array with the expanding statistic
***
## function `expanding_min`
```python theme={null}
expanding_min(x: ndarray) → ndarray
```
Compute the expanding\_min of the input array.
**Args:**
* `x` (np.ndarray): Input array.
**Returns:**
* `np.ndarray`: Array with the expanding statistic
***
## function `expanding_max`
```python theme={null}
expanding_max(x: ndarray) → ndarray
```
Compute the expanding\_max of the input array.
**Args:**
* `x` (np.ndarray): Input array.
**Returns:**
* `np.ndarray`: Array with the expanding statistic
***
## function `expanding_quantile`
```python theme={null}
expanding_quantile(x: ndarray, p: float) → ndarray
```
Compute the expanding\_quantile of the input array.
**Args:**
* `x` (np.ndarray): Input array.
* `p` (float): Quantile to compute.
**Returns:**
* `np.ndarray`: Array with the expanding statistic
***
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