statsmodels.sandbox.stats.runs.runstest_2samp statsmodels.sandbox.stats.runs.runstest_2samp(x, y=None, groups=None, correction=True) [source] Wald-Wolfowitz runstest for two samples This tests whether two samples come from the same distribution. Parameters: x : array_like data, numeric, contains either one group, if y is also given, or both groups, if additionally a group indicator is provided y : array_like (optional) data, numeric groups : array_like group labels or indicator the dat

statsmodels.graphics.boxplots.beanplot statsmodels.graphics.boxplots.beanplot(data, ax=None, labels=None, positions=None, side='both', jitter=False, plot_opts={}) [source] Make a bean plot of each dataset in the data sequence. A bean plot is a combination of a violinplot (kernel density estimate of the probability density function per point) with a line-scatter plot of all individual data points. Parameters: data : sequence of ndarrays Data arrays, one array per value in positions. ax : M

statsmodels.stats.weightstats.DescrStatsW class statsmodels.stats.weightstats.DescrStatsW(data, weights=None, ddof=0) [source] descriptive statistics and tests with weights for case weights Assumes that the data is 1d or 2d with (nobs, nvars) observations in rows, variables in columns, and that the same weight applies to each column. If degrees of freedom correction is used, then weights should add up to the number of observations. ttest also assumes that the sum of weights corresponds to th

statsmodels.sandbox.regression.gmm.IVGMM.fitstart IVGMM.fitstart() [source]

statsmodels.discrete.discrete_model.ProbitResults.llf static ProbitResults.llf()

statsmodels.tsa.arima_model.ARIMAResults.arparams static ARIMAResults.arparams()

statsmodels.discrete.discrete_model.ProbitResults.tvalues static ProbitResults.tvalues() Return the t-statistic for a given parameter estimate.

statsmodels.regression.linear_model.OLS.fit_regularized OLS.fit_regularized(method='coord_descent', maxiter=1000, alpha=0.0, L1_wt=1.0, start_params=None, cnvrg_tol=1e-08, zero_tol=1e-08, **kwargs) Return a regularized fit to a linear regression model. Parameters: method : string Only the coordinate descent algorithm is implemented. maxiter : integer The maximum number of iteration cycles (an iteration cycle involves running coordinate descent on all variables). alpha : scalar or array-

Tools Our tool collection contains some convenience functions for users and functions that were written mainly for internal use. Additional to this tools directory, several other subpackages have their own tools modules, for example statsmodels.tsa.tsatools Module Reference Basic tools tools These are basic and miscellaneous tools. The full import path is statsmodels.tools.tools. tools.add_constant(data[, prepend, has_constant]) This appends a column of ones to an array if prepend==False.

statsmodels.iolib.table.SimpleTable.as_csv SimpleTable.as_csv(**fmt_dict) [source] Return string, the table in CSV format. Currently only supports comma separator.