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Statsmodels is a Python package that provides a complement to scipy for statistical computations including descriptive statistics and estimation and inference for statistical models. Main Features: * linear regression models: GLS (including WLS and LS aith AR errors) and OLS. * glm: Generalized linear models with support for all of the one-parameter exponential family distributions. * discrete: regression with discrete dependent variables, including Logit, Probit, MNLogit, Poisson, based on maximum likelihood estimators * rlm: Robust linear models with support for several M-estimators. * tsa: models for time series analysis - univariate: AR, ARIMA; multivariate: VAR and structural VAR * nonparametric: (Univariate) kernel density estimators * datasets: Datasets to be distributed and used for examples and in testing. * stats: a wide range of statistical tests, diagnostics and specification tests * iolib: Tools for reading Stata .dta files into numpy arrays, printing table output to ascii, latex, and html * miscellaneous models * sandbox: statsmodels contains a sandbox folder with code in various stages of * developement and testing which is not considered "production ready", including Mixed models, GARCH and GMM estimators, kernel regression, panel data models. WWW: https://www.github.com/statsmodels/statsmodels PR: ports/183932 Submitted by: Johannes Jost Meixner <xmj chaot.net>
2124 lines
132 KiB
Plaintext
2124 lines
132 KiB
Plaintext
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