statsmodels.duration.hazard_regression.PHReg.get_distribution PHReg.get_distribution(params) [source] Returns a scipy distribution object corresponding to the distribution of uncensored endog (duration) values for each case. Parameters: params : arrayh-like The model proportional hazards model parameters. Returns: A list of objects of type scipy.stats.distributions.rv_discrete : Notes The distributions are obtained from a simple discrete estimate of the survivor function that puts all

statsmodels.sandbox.tsa.fftarma.ArmaFft.spdroots ArmaFft.spdroots_(arroots, maroots, w) [source] spectral density for frequency using polynomial roots builds two arrays (number of roots, number of frequencies) Parameters: arroots : ndarray roots of ar (denominator) lag-polynomial maroots : ndarray roots of ma (numerator) lag-polynomial w : array_like frequencies for which spd is calculated Notes this should go into a function

statsmodels.graphics.regressionplots.influence_plot statsmodels.graphics.regressionplots.influence_plot(results, external=True, alpha=0.05, criterion='cooks', size=48, plot_alpha=0.75, ax=None, **kwargs) [source] Plot of influence in regression. Plots studentized resids vs. leverage. Parameters: results : results instance A fitted model. external : bool Whether to use externally or internally studentized residuals. It is recommended to leave external as True. alpha : float The alpha va

statsmodels.sandbox.distributions.transformed.Transf_gen.fit_loc_scale Transf_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.NormExpan_gen.pdf NormExpan_gen.pdf(x, *args, **kwds) Probability density function at x 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: pdf : ndarray Probability density funct

statsmodels.stats.power.TTestIndPower.solve_power TTestIndPower.solve_power(effect_size=None, nobs1=None, alpha=None, power=None, ratio=1.0, alternative='two-sided') [source] solve for any one parameter of the power of a two sample t-test for t-test the keywords are: effect_size, nobs1, alpha, power, ratio exactly one needs to be None, all others need numeric values Parameters: effect_size : float standardized effect size, difference between the two means divided by the standard deviation.

statsmodels.sandbox.distributions.transformed.TransfTwo_gen.fit_loc_scale TransfTwo_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.SkewNorm_gen.sf SkewNorm_gen.sf(x, *args, **kwds) Survival function (1-cdf) at x 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: sf : array_like Survival function evaluated at

statsmodels.sandbox.distributions.extras.NormExpan_gen.ppf NormExpan_gen.ppf(q, *args, **kwds) Percent point function (inverse of cdf) at q of the given RV. Parameters: q : array_like lower tail probability 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: x : array_like

statsmodels.sandbox.distributions.extras.NormExpan_gen.sf NormExpan_gen.sf(x, *args, **kwds) Survival function (1-cdf) at x 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: sf : array_like Survival function evaluated