statsmodels.discrete.discrete_model.ProbitResults.wald_test ProbitResults.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

statsmodels.discrete.discrete_model.BinaryResults.bic static BinaryResults.bic()

Autoregressive Moving Average (ARMA): Artificial data Link to Notebook GitHub In [1]: from __future__ import print_function import numpy as np import statsmodels.api as sm import pandas as pd from statsmodels.tsa.arima_process import arma_generate_sample np.random.seed(12345) Generate some data from an ARMA process: In [2]: arparams = np.array([.75, -.25]) maparams = np.array([.65, .35]) The conventions of the arma_generate function require that we specify a 1 f

statsmodels.tsa.ar_model.ARResults.t_test ARResults.t_test(r_matrix, cov_p=None, scale=None, use_t=None) Compute a t-test for a each linear hypothesis of the form Rb = q Parameters: r_matrix : array-like, str, tuple array : If an array is given, a p x k 2d array or length k 1d array specifying the linear restrictions. 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 of arrays in the for

statsmodels.genmod.generalized_estimating_equations.GEEResults.wald_test GEEResults.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.

Discrete Choice Models Link to Notebook GitHub Fair's Affair data A survey of women only was conducted in 1974 by Redbook asking about extramarital affairs. In [1]: from __future__ import print_function import numpy as np from scipy import stats import matplotlib.pyplot as plt import statsmodels.api as sm from statsmodels.formula.api import logit, probit, poisson, ols In [2]: print(sm.datasets.fair.SOURCE) Fair, Ray. 1978. "A Theory of Extramarital Affa

statsmodels.discrete.discrete_model.BinaryResults.save BinaryResults.save(fname, remove_data=False) save a pickle of this instance Parameters: fname : string or filehandle fname can be a string to a file path or filename, or a filehandle. remove_data : bool If False (default), then the instance is pickled without changes. If True, then all arrays with length nobs are set to None before pickling. See the remove_data method. In some cases not all arrays will be set to None. Notes If remo

statsmodels.sandbox.distributions.transformed.negsquarenormalg statsmodels.sandbox.distributions.transformed.negsquarenormalg = Distribution based on a non-monotonic (u- or hump-shaped transformation) the constructor can be called with a distribution class, and functions that define the non-linear transformation. and generates the distribution of the transformed random variable Note: the transformation, it?s inverse and derivatives need to be fully specified: func, funcinvplus, funcinvminus

statsmodels.duration.hazard_regression.PHRegResults.wald_test PHRegResults.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

statsmodels.stats.weightstats.DescrStatsW.std_mean static DescrStatsW.std_mean() [source] standard deviation of weighted mean