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Module « scipy.stats.mstats »

Fonction spearmanr - module scipy.stats.mstats

Signature de la fonction spearmanr

def spearmanr(x, y=None, use_ties=True, axis=None, nan_policy='propagate', alternative='two-sided') 

Description

help(scipy.stats.mstats.spearmanr)

Calculates a Spearman rank-order correlation coefficient and the p-value
to test for non-correlation.

The Spearman correlation is a nonparametric measure of the linear
relationship between two datasets. Unlike the Pearson correlation, the
Spearman correlation does not assume that both datasets are normally
distributed. Like other correlation coefficients, this one varies
between -1 and +1 with 0 implying no correlation. Correlations of -1 or
+1 imply a monotonic relationship. Positive correlations imply that
as `x` increases, so does `y`. Negative correlations imply that as `x`
increases, `y` decreases.

Missing values are discarded pair-wise: if a value is missing in `x`, the
corresponding value in `y` is masked.

The p-value roughly indicates the probability of an uncorrelated system
producing datasets that have a Spearman correlation at least as extreme
as the one computed from these datasets. The p-values are not entirely
reliable but are probably reasonable for datasets larger than 500 or so.

Parameters
----------
x, y : 1D or 2D array_like, y is optional
    One or two 1-D or 2-D arrays containing multiple variables and
    observations. When these are 1-D, each represents a vector of
    observations of a single variable. For the behavior in the 2-D case,
    see under ``axis``, below.
use_ties : bool, optional
    DO NOT USE.  Does not do anything, keyword is only left in place for
    backwards compatibility reasons.
axis : int or None, optional
    If axis=0 (default), then each column represents a variable, with
    observations in the rows. If axis=1, the relationship is transposed:
    each row represents a variable, while the columns contain observations.
    If axis=None, then both arrays will be raveled.
nan_policy : {'propagate', 'raise', 'omit'}, optional
    Defines how to handle when input contains nan. 'propagate' returns nan,
    'raise' throws an error, 'omit' performs the calculations ignoring nan
    values. Default is 'propagate'.
alternative : {'two-sided', 'less', 'greater'}, optional
    Defines the alternative hypothesis. Default is 'two-sided'.
    The following options are available:

    * 'two-sided': the correlation is nonzero
    * 'less': the correlation is negative (less than zero)
    * 'greater':  the correlation is positive (greater than zero)

    .. versionadded:: 1.7.0

Returns
-------
res : SignificanceResult
    An object containing attributes:

    statistic : float or ndarray (2-D square)
        Spearman correlation matrix or correlation coefficient (if only 2
        variables are given as parameters). Correlation matrix is square
        with length equal to total number of variables (columns or rows) in
        ``a`` and ``b`` combined.
    pvalue : float
        The p-value for a hypothesis test whose null hypothesis
        is that two sets of data are linearly uncorrelated. See
        `alternative` above for alternative hypotheses. `pvalue` has the
        same shape as `statistic`.

References
----------
[CRCProbStat2000] section 14.7

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