statsmodels.genmod.families.links.probit.inverse probit.inverse(z) The inverse of the CDF link Parameters: z : array-like The value of the inverse of the link function at p Returns: p : array Mean probabilities. The value of the inverse of CDF link of z Notes g^(-1)(z) = dbn.cdf(z)

statsmodels.regression.quantile_regression.QuantRegResults.HC1_se static QuantRegResults.HC1_se() [source]

statsmodels.tsa.arima_model.ARMAResults.tvalues static ARMAResults.tvalues() Return the t-statistic for a given parameter estimate.

statsmodels.regression.linear_model.OLSResults.llf static OLSResults.llf()

statsmodels.duration.hazard_regression.PHRegResults.standard_errors static PHRegResults.standard_errors() [source] Returns the standard errors of the parameter estimates.

statsmodels.tools.tools.clean0 statsmodels.tools.tools.clean0(matrix) [source] Erase columns of zeros: can save some time in pseudoinverse.

statsmodels.discrete.discrete_model.DiscreteModel.hessian DiscreteModel.hessian(params) The Hessian matrix of the model

statsmodels.sandbox.distributions.extras.ACSkewT_gen.expect ACSkewT_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 argument.

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

statsmodels.tsa.vector_ar.var_model.VAR.predict VAR.predict(params, start=None, end=None, lags=1, trend='c') [source] Returns in-sample predictions or forecasts