statsmodels.sandbox.distributions.extras.mvnormcdf statsmodels.sandbox.distributions.extras.mvnormcdf(upper, mu, cov, lower=None, **kwds) [source] multivariate normal cumulative distribution function This is a wrapper for scipy.stats.kde.mvn.mvndst which calculates a rectangular integral over a multivariate normal distribution. Parameters: lower, upper : array_like, 1d lower and upper integration limits with length equal to the number of dimensions of the multivariate normal distribution.

statsmodels.discrete.discrete_model.MultinomialResults.llr static MultinomialResults.llr()

statsmodels.robust.scale.hubers_scale statsmodels.robust.scale.hubers_scale = Huber?s scaling for fitting robust linear models. Huber?s scale is intended to be used as the scale estimate in the IRLS algorithm and is slightly different than the Huber class. Parameters: d : float, optional d is the tuning constant for Huber?s scale. Default is 2.5 tol : float, optional The convergence tolerance maxiter : int, optiona The maximum number of iterations. The default is 30. Notes Huber?s s

statsmodels.robust.scale.mad statsmodels.robust.scale.mad(a, c=0.67448975019608171, axis=0, center=) [source] The Median Absolute Deviation along given axis of an array Parameters: a : array-like Input array. c : float, optional The normalization constant. Defined as scipy.stats.norm.ppf(3/4.), which is approximately .6745. axis : int, optional The defaul is 0. Can also be None. center : callable or float If a callable is provided, such as the default np.median then it is expected to

statsmodels.stats.weightstats.DescrStatsW.get_compare DescrStatsW.get_compare(other, weights=None) [source] return an instance of CompareMeans with self and other Parameters: other : array_like or instance of DescrStatsW If array_like then this creates an instance of DescrStatsW with the given weights. weights : None or array weights are only used if other is not an instance of DescrStatsW Returns: cm : instance of CompareMeans the instance has self attached as d1 and other as d2.

statsmodels.sandbox.tsa.fftarma.ArmaFft.spdroots ArmaFft.spdroots(w) [source] spectral density for frequency using polynomial roots builds two arrays (number of roots, number of frequencies)

statsmodels.genmod.families.family.InverseGaussian class statsmodels.genmod.families.family.InverseGaussian(link=) [source] InverseGaussian exponential family. Parameters: link : a link instance, optional The default link for the inverse Gaussian family is the inverse squared link. Available links are inverse_squared, inverse, log, and identity. See statsmodels.family.links for more information. See also statsmodels.genmod.families.family.Family, Link Functions Notes The inverse Guassi

statsmodels.graphics.gofplots.ProbPlot.qqplot ProbPlot.qqplot(xlabel=None, ylabel=None, line=None, other=None, ax=None, **plotkwargs) [source] Q-Q plot of the quantiles of x versus the quantiles/ppf of a distribution or the quantiles of another ProbPlot instance. Parameters: xlabel, ylabel : str or None, optional User-provided lables for the x-axis and y-axis. If None (default), other values are used depending on the status of the kwarg other. line : str {?45?, ?s?, ?r?, q?} or None, opti

statsmodels.regression.linear_model.OLSResults.wald_test OLSResults.wald_test(r_matrix, cov_p=None, scale=1.0, invcov=None, use_f=None) Compute a Wald-test for a joint linear hypothesis. Parameters: r_matrix : array-like, str, or tuple array : An r x k array where r is the number of restrictions to test and k is the number of regressors. It is assumed that the linear combination is equal to zero. str : The full hypotheses to test can be given as a string. See the examples. tuple : A tuple

statsmodels.emplike.descriptive.DescStatMV.test_corr DescStatMV.test_corr(corr0, return_weights=0) [source] Returns -2 x log-likelihood ratio and p-value for the correlation coefficient between 2 variables Parameters: corr0 : float Hypothesized value to be tested return_weights : bool If true, returns the weights that maximize the log-likelihood at the hypothesized value