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# skfolio.distribution.select_univariate_dist

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### skfolio.distribution.select_univariate_dist(X, distribution_candidates=None, selection_criterion=AIC)

Select the optimal univariate distribution estimator based on an information
criterion.

For each candidate distribution, the function fits the distribution to X and then
computes either the Akaike Information Criterion (AIC) or the Bayesian Information
Criterion (BIC). The candidate with the lowest criterion value is returned.

* **Parameters:**
  **X** *array-like of shape (n_observations, 1)*
  : The input data used to fit each candidate distribution.

  **distribution_candidates** *list of BaseUnivariateDist*
  : A list of candidate distribution estimators. Each candidate must be an instance
    of a class that inherits from `BaseUnivariateDist`.
    If None, defaults to `[Gaussian(), StudentT(), JohnsonSU()]`.

  **selection_criterion** *SelectionCriterion, default=SelectionCriterion.AIC*
  : The criterion used for model selection. Possible values are:
    : - SelectionCriterion.AIC : Akaike Information Criterion
      - SelectionCriterion.BIC : Bayesian Information Criterion
* **Returns:**
  BaseUnivariateDist
  : The fitted candidate estimator that minimizes the selected information
    criterion.
* **Raises:**
  ValueError
  : If X does not have exactly one column or if any candidate in the list does not
    inherit from BaseUnivariateDist.