# estimation.detect_singletons

    estimation.detect_singletons(ids)

Detect singleton fixed effects in a dataset.

This function iterates over the columns of a 2D numpy array representing fixed effects to identify singleton fixed effects. An observation is considered a singleton if it is the only one in its group (fixed effect identifier).

## Parameters

Name | Type | Description | Default
--- | --- | --- | ---
ids | np.ndarray | A 2D numpy array representing fixed effects, with a shape of (n_samples, n_features). Elements should be non-negative integers representing fixed effect identifiers. | required

## Returns

Name | Type | Description
--- | --- | ---
| numpy.ndarray | A boolean array of shape (n_samples,), indicating which observations have a singleton fixed effect.

## Notes

The algorithm iterates over columns to identify fixed effects. After each column is processed, it updates the record of non-singleton rows. This approach accounts for the possibility that removing an observation in one column can lead to the emergence of new singletons in subsequent columns.

For performance reasons, the input array should be in column-major order. Operating on a row-major array can lead to significant performance losses.