3. Main modules of interest¶

3.1. statsmodel¶

`statsmodels.discrete.discrete_margins`
`statsmodels.discrete.discrete_model`	Limited dependent variable and qualitative variables.

`statsmodels.distributions`
`statsmodels.distributions.edgeworth`
`statsmodels.distributions.empirical_distribution`	Empirical CDF Functions
`statsmodels.distributions.mixture_rvs`

`statsmodels.emplike.api`	api for empirical likelihood
`statsmodels.emplike.aft_el`	Accelerated Failure Time (AFT) Model with empirical likelihood inference.
`statsmodels.emplike.descriptive`	Empirical likelihood inference on descriptive statistics
`statsmodels.emplike.elanova`	This script contains empirical likelihood ANOVA.
`statsmodels.emplike.elregress`	Empirical Likelihood Linear Regression Inference
`statsmodels.emplike.originregress`	This module implements empirical likelihood regression that is forced through the origin.

`statsmodels.genmod.api`
`statsmodels.genmod.cov_struct`
`statsmodels.genmod.generalized_estimating_equations`	Procedures for fitting marginal regression models to dependent data using Generalized Estimating Equations.
`statsmodels.genmod.generalized_linear_model`	Generalized linear models currently supports estimation using the one-parameter

`statsmodels.genmod.families`	This module contains the one-parameter exponential families used for fitting GLMs and GAMs.
`statsmodels.genmod.families.family`	The one parameter exponential family distributions used by GLM.
`statsmodels.genmod.families.links`	Defines the link functions to be used with GLM and GEE families.
`statsmodels.genmod.families.varfuncs`	Variance functions for use with the link functions in statsmodels.family.links

`statsmodels.graphics.api`
`statsmodels.graphics.boxplots`	Variations on boxplots.
`statsmodels.graphics.correlation`	correlation plots
`statsmodels.graphics.dotplots`
`statsmodels.graphics.factorplots`	Authors: Josef Perktold, Skipper Seabold, Denis A.
`statsmodels.graphics.functional`	Module for functional boxplots.
`statsmodels.graphics.gofplots`
`statsmodels.graphics.mosaicplot`	Create a mosaic plot from a contingency table.
`statsmodels.graphics.plot_grids`	create scatterplot with confidence ellipsis
`statsmodels.graphics.plottools`
`statsmodels.graphics.regressionplots`	Partial Regression plot and residual plots to find misspecification
`statsmodels.graphics.tsaplots`	Correlation plot functions.
`statsmodels.graphics.tukeyplot`
`statsmodels.graphics.utils`	Helper functions for graphics with Matplotlib.

`statsmodels.miscmodels.api`
`statsmodels.miscmodels.count`	Created on Mon Jul 26 08:34:59 2010
`statsmodels.miscmodels.nonlinls`	Non-linear least squares
`statsmodels.miscmodels.tmodel`	Linear Model with Student-t distributed errors
`statsmodels.miscmodels.try_mlecov`	Multivariate Normal Model with full covariance matrix

`statsmodels.nonparametric.api`
`statsmodels.nonparametric.bandwidths`
`statsmodels.nonparametric.kde`	Univariate Kernel Density Estimators
`statsmodels.nonparametric.kdetools`
`statsmodels.nonparametric.kernel_density`	Multivariate Conditional and Unconditional Kernel Density Estimation with Mixed Data Types.
`statsmodels.nonparametric.kernel_regression`	Multivariate Conditional and Unconditional Kernel Density Estimation
`statsmodels.nonparametric.kernels`	Module of kernels that are able to handle continuous as well as categorical variables (both ordered and unordered).
`statsmodels.nonparametric.smoothers_lowess_old`	Univariate lowess function, like in R.
`statsmodels.nonparametric.smoothers_lowess`	Lowess - wrapper for cythonized extension

`statsmodels.regression.feasible_gls`	Created on Tue Dec 20 20:24:20 2011
`statsmodels.regression.linear_model`	This module implements standard regression models:
`statsmodels.regression.mixed_linear_model`	Linear mixed effects models for Statsmodels
`statsmodels.regression.quantile_regression`	Quantile regression model

`statsmodels.robust.norms`
`statsmodels.robust.robust_linear_model`	Robust linear models with support for the M-estimators listed under norms.
`statsmodels.robust.scale`	Support and standalone functions for Robust Linear Models

`statsmodels.stats.api`
`statsmodels.stats.adnorm`	Created on Sun Sep 25 21:23:38 2011
`statsmodels.stats.anova`
`statsmodels.stats.base`	Base classes for statistical test results
`statsmodels.stats.contrast`
`statsmodels.stats.correlation_tools`	Created on Fri Aug 17 13:10:52 2012
`statsmodels.stats.descriptivestats`
`statsmodels.stats.diagnostic`
`statsmodels.stats.gof`	extra statistical function and helper functions
`statsmodels.stats.inter_rater`	Inter Rater Agreement
`statsmodels.stats.lilliefors`	Created on Sat Oct 01 13:16:49 2011
`statsmodels.stats.moment_helpers`	helper functions conversion between moments
`statsmodels.stats.multicomp`	Created on Fri Mar 30 18:27:25 2012
`statsmodels.stats.multitest`	Multiple Testing and P-Value Correction
`statsmodels.stats.multivariate_tools`	Tools for multivariate analysis
`statsmodels.stats.outliers_influence`	Influence and Outlier Measures
`statsmodels.stats.power`	Statistical power, solving for nobs, ...
`statsmodels.stats.proportion`	Tests and Confidence Intervals for Binomial Proportions
`statsmodels.stats.sandwich_covariance`	Sandwich covariance estimators
`statsmodels.stats.stattools`	Statistical tests to be used in conjunction with the models
`statsmodels.stats.tabledist`	Created on Sat Oct 01 20:20:16 2011
`statsmodels.stats.weightstats`	Ttests and descriptive statistics with weights