6. statsmodel.sandbox2¶

More sandbox (in subfolders)

6.1. statsmodels.sandbox.archive¶

`statsmodels.sandbox.archive.linalg_covmat`
`statsmodels.sandbox.archive.linalg_decomp_1`	Recipes for more efficient work with linalg using classes
`statsmodels.sandbox.archive.tsa`	Collection of alternative implementations for time series analysis

`statsmodels.sandbox.datarich`	Econometrics for a Datarich Environment
`statsmodels.sandbox.datarich.factormodels`	Created on Sun Nov 14 08:21:41 2010

`statsmodels.sandbox.distributions`	temporary location for enhancements to scipy.stats
`statsmodels.sandbox.distributions.copula`	Which Archimedean is Best?
`statsmodels.sandbox.distributions.estimators`	estimate distribution parameters by various methods
`statsmodels.sandbox.distributions.extras`	Various extensions to distributions
`statsmodels.sandbox.distributions.genpareto`	Created on Thu Aug 12 14:59:03 2010
`statsmodels.sandbox.distributions.gof_new`	More Goodness of fit tests
`statsmodels.sandbox.distributions.multivariate`	Multivariate Distribution
`statsmodels.sandbox.distributions.mv_measures`	using multivariate dependence and divergence measures
`statsmodels.sandbox.distributions.mv_normal`	Multivariate Normal and t distributions
`statsmodels.sandbox.distributions.otherdist`	Parametric Mixture Distributions
`statsmodels.sandbox.distributions.quantize`	Quantizing a continuous distribution in 2d
`statsmodels.sandbox.distributions.sppatch`	patching scipy to fit distributions and expect method
`statsmodels.sandbox.distributions.transform_functions`	Nonlinear Transformation classes
`statsmodels.sandbox.distributions.transformed`	A class for the distribution of a non-linear monotonic transformation of a continuous random variable
`statsmodels.sandbox.distributions.try_max`	adjusted from Denis on pystatsmodels mailing list
`statsmodels.sandbox.distributions.try_pot`	Created on Wed May 04 06:09:18 2011

`statsmodels.sandbox.mcevaluate`	Econometrics for a Datarich Environment
`statsmodels.sandbox.mcevaluate.arma`

`statsmodels.sandbox.nonparametric.densityorthopoly`	density estimation based on orthogonal polynomials
`statsmodels.sandbox.nonparametric.dgp_examples`	Examples of non-linear functions for non-parametric regression
`statsmodels.sandbox.nonparametric.kde2`
`statsmodels.sandbox.nonparametric.kdecovclass`	subclassing kde
`statsmodels.sandbox.nonparametric.kernel_extras`	Multivariate Conditional and Unconditional Kernel Density Estimation
`statsmodels.sandbox.nonparametric.kernels`	This models contains the Kernels for Kernel smoothing.
`statsmodels.sandbox.nonparametric.smoothers`	This module contains scatterplot smoothers, that is classes who generate a smooth fit of a set of (x,y) pairs.
`statsmodels.sandbox.nonparametric.testdata`	Created on Fri Mar 04 07:36:28 2011

`statsmodels.sandbox.panel.correlation_structures`	Correlation and Covariance Structures
`statsmodels.sandbox.panel.mixed`	Mixed effects models
`statsmodels.sandbox.panel.panel_short`	Panel data analysis for short T and large N
`statsmodels.sandbox.panel.random_panel`	Generate a random process with panel structure
`statsmodels.sandbox.panel.sandwich_covariance_generic`	covariance with (nobs,nobs) loop and general kernel
`statsmodels.sandbox.panel.sandwich_covariance`	temporary compatibility module

`statsmodels.sandbox.regression.anova_nistcertified`	calculating anova and verifying with NIST test data
`statsmodels.sandbox.regression.ar_panel`	Paneldata model with fixed effect (constants) and AR(1) errors
`statsmodels.sandbox.regression.example_kernridge`
`statsmodels.sandbox.regression.gmm`	Generalized Method of Moments, GMM, and Two-Stage Least Squares for
`statsmodels.sandbox.regression.kernridgeregress_class`	Kernel Ridge Regression for local non-parametric regression
`statsmodels.sandbox.regression.onewaygls`	F test for null hypothesis that coefficients in several regressions are the same
`statsmodels.sandbox.regression.penalized`	linear model with Theil prior probabilistic restrictions, generalized Ridge
`statsmodels.sandbox.regression.predstd`	Additional functions
`statsmodels.sandbox.regression.sympy_diff`	Created on Sat Mar 13 07:56:22 2010
`statsmodels.sandbox.regression.tools`	gradient/Jacobian of normal and t loglikelihood
`statsmodels.sandbox.regression.treewalkerclass`	Formulas
`statsmodels.sandbox.regression.try_catdata`
`statsmodels.sandbox.regression.try_ols_anova`	convenience functions for ANOVA type analysis with OLS
`statsmodels.sandbox.regression.try_treewalker`	Trying out tree structure for nested logit

`statsmodels.sandbox.stats`	temporary location for enhancements to scipy.stats
`statsmodels.sandbox.stats.contrast_tools`	functions to work with contrasts for multiple tests
`statsmodels.sandbox.stats.diagnostic`	Various Statistical Tests
`statsmodels.sandbox.stats.ex_newtests`
`statsmodels.sandbox.stats.multicomp`	from pystatsmodels mailinglist 20100524
`statsmodels.sandbox.stats.runs`	runstest
`statsmodels.sandbox.stats.stats_dhuard`	from David Huard’s scipy sandbox, also attached to a ticket and
`statsmodels.sandbox.stats.stats_mstats_short.py`

`statsmodels.sandbox.tests`	Econometrics for a Datarich Environment
`statsmodels.sandbox.tests.datamlw`
`statsmodels.sandbox.tests.maketests_mlabwrap`	generate py modules with test cases and results from mlabwrap
`statsmodels.sandbox.tests.model_results`	This should be merged into statsmodels/tests/model_results.py when things move out of the sandbox.
`statsmodels.sandbox.tests.savervs`	generates some ARMA random samples and saves to python module file
`statsmodels.sandbox.tests.test_formula`	Test functions for models.formula
`statsmodels.sandbox.tests.test_gam`	Tests for gam.AdditiveModel and GAM with Polynomials compared to OLS and GLM
`statsmodels.sandbox.tests.test_pca`	tests for pca and arma to ar and ma representation

`statsmodels.sandbox.tools`	some helper function for principal component and time series analysis
`statsmodels.sandbox.tools.cross_val`	Utilities for cross validation.
`statsmodels.sandbox.tools.mctools`	Helper class for Monte Carlo Studies for (currently) statistical tests
`statsmodels.sandbox.tools.tools_pca`	Principal Component Analysis
`statsmodels.sandbox.tools.try_mctools`	Created on Fri Sep 30 15:20:45 2011

`statsmodels.sandbox.tsa`	functions and classes time series analysis
`statsmodels.sandbox.tsa.diffusion`	getting started with diffusions, continuous time stochastic processes
`statsmodels.sandbox.tsa.diffusion2`	Diffusion 2: jump diffusion, stochastic volatility, stochastic time
`statsmodels.sandbox.tsa.example_arma`
`statsmodels.sandbox.tsa.fftarma`	Created on Mon Dec 14 19:53:25 2009
`statsmodels.sandbox.tsa.garch`
`statsmodels.sandbox.tsa.movstat`	using scipy signal and numpy correlate to calculate some time series
`statsmodels.sandbox.tsa.try_arma_more`	Periodograms for ARMA and time series
`statsmodels.sandbox.tsa.try_fi`	using lfilter to get fractional integration polynomial (1-L)^d, d<1
`statsmodels.sandbox.tsa.try_var_convolve`
`statsmodels.sandbox.tsa.varma`	VAR and VARMA process