Module « scipy.stats »

Fonction jarque_bera - module scipy.stats

Signature de la fonction jarque_bera

def jarque_bera(x) 

Description

jarque_bera.__doc__

Perform the Jarque-Bera goodness of fit test on sample data.

    The Jarque-Bera test tests whether the sample data has the skewness and
    kurtosis matching a normal distribution.

    Note that this test only works for a large enough number of data samples
    (>2000) as the test statistic asymptotically has a Chi-squared distribution
    with 2 degrees of freedom.

    Parameters
    ----------
    x : array_like
        Observations of a random variable.

    Returns
    -------
    jb_value : float
        The test statistic.
    p : float
        The p-value for the hypothesis test.

    References
    ----------
    .. [1] Jarque, C. and Bera, A. (1980) "Efficient tests for normality,
           homoscedasticity and serial independence of regression residuals",
           6 Econometric Letters 255-259.

    Examples
    --------
    >>> from scipy import stats
    >>> rng = np.random.default_rng()
    >>> x = rng.normal(0, 1, 100000)
    >>> jarque_bera_test = stats.jarque_bera(x)
    >>> jarque_bera_test
    Jarque_beraResult(statistic=3.3415184718131554, pvalue=0.18810419594996775)
    >>> jarque_bera_test.statistic
    3.3415184718131554
    >>> jarque_bera_test.pvalue
    0.18810419594996775