statsmodels.sandbox.distributions.extras.SkewNorm2_gen.fit_loc_scale SkewNorm2_gen.fit_loc_scale(data, *args) Estimate loc and scale parameters from data using 1st and 2nd moments. Parameters: data : array_like Data to fit. arg1, arg2, arg3,... : array_like The shape parameter(s) for the distribution (see docstring of the instance object for more information). Returns: Lhat : float Estimated location parameter for the data. Shat : float Estimated scale parameter for the data.

statsmodels.sandbox.distributions.extras.SkewNorm2_gen.fit SkewNorm2_gen.fit(data, *args, **kwds) Return MLEs for shape, location, and scale parameters from data. MLE stands for Maximum Likelihood Estimate. Starting estimates for the fit are given by input arguments; for any arguments not provided with starting estimates, self._fitstart(data) is called to generate such. One can hold some parameters fixed to specific values by passing in keyword arguments f0, f1, ..., fn (for shape parameters

statsmodels.sandbox.distributions.extras.SkewNorm2_gen.est_loc_scale SkewNorm2_gen.est_loc_scale(*args, **kwds) est_loc_scale is deprecated! This function is deprecated, use self.fit_loc_scale(data) instead.

statsmodels.sandbox.distributions.extras.SkewNorm2_gen.expect SkewNorm2_gen.expect(func=None, args=(), loc=0, scale=1, lb=None, ub=None, conditional=False, **kwds) Calculate expected value of a function with respect to the distribution. The expected value of a function f(x) with respect to a distribution dist is defined as: ubound E[x] = Integral(f(x) * dist.pdf(x)) lbound Parameters: func : callable, optional Function for which integral is calculated. Takes only one argum

statsmodels.iolib.table.SimpleTable.sort SimpleTable.sort() L.sort(cmp=None, key=None, reverse=False) ? stable sort IN PLACE; cmp(x, y) -> -1, 0, 1

statsmodels.sandbox.distributions.extras.SkewNorm2_gen.cdf SkewNorm2_gen.cdf(x, *args, **kwds) Cumulative distribution function of the given RV. Parameters: x : array_like quantiles arg1, arg2, arg3,... : array_like The shape parameter(s) for the distribution (see docstring of the instance object for more information) loc : array_like, optional location parameter (default=0) scale : array_like, optional scale parameter (default=1) Returns: cdf : ndarray Cumulative distribution fu

statsmodels.sandbox.distributions.extras.SkewNorm2_gen.entropy SkewNorm2_gen.entropy(*args, **kwds) Differential entropy of the RV. Parameters: arg1, arg2, arg3,... : array_like The shape parameter(s) for the distribution (see docstring of the instance object for more information). loc : array_like, optional Location parameter (default=0). scale : array_like, optional Scale parameter (default=1).

statsmodels.iolib.table.SimpleTable.reverse SimpleTable.reverse() L.reverse() ? reverse IN PLACE

statsmodels.iolib.table.SimpleTable.remove SimpleTable.remove() L.remove(value) ? remove first occurrence of value. Raises ValueError if the value is not present.

statsmodels.iolib.table.SimpleTable.pop SimpleTable.pop([index]) ? item -- remove and return item at index (default last). Raises IndexError if list is empty or index is out of range.