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StatsModels: Statistics in Python — statsmodels 0.6.1 documentation

Welcome to Statsmodels’s Documentation. You can use R-style formulas together with. Data frames to fit your models. Here is a simple example using ordinary least squares:. Fit regression model (using the natural log of one of the regressors). ******* Literacy np.log(Pop1831). You can also use. Arrays instead of formulas:. Generate artificial data (2 regressors constant). Have a look at. To see available results. Attributes are described in. And results methods have their own docstrings. Information about...

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StatsModels: Statistics in Python — statsmodels 0.6.1 documentation | statsmodels.org Reviews

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Welcome to Statsmodels’s Documentation. You can use R-style formulas together with. Data frames to fit your models. Here is a simple example using ordinary least squares:. Fit regression model (using the natural log of one of the regressors). ******* Literacy np.log(Pop1831). You can also use. Arrays instead of formulas:. Generate artificial data (2 regressors constant). Have a look at. To see available results. Attributes are described in. And results methods have their own docstrings. Information about...

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StatsModels: Statistics in Python — statsmodels 0.6.1 documentation | statsmodels.org Reviews

https://statsmodels.org

Welcome to Statsmodels’s Documentation. You can use R-style formulas together with. Data frames to fit your models. Here is a simple example using ordinary least squares:. Fit regression model (using the natural log of one of the regressors). ******* Literacy np.log(Pop1831). You can also use. Arrays instead of formulas:. Generate artificial data (2 regressors constant). Have a look at. To see available results. Attributes are described in. And results methods have their own docstrings. Information about...

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statsmodels.org

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Statsmodels Examples — statsmodels 0.6.1 documentation

http://www.statsmodels.org/stable/examples/index.html

This page provides a series of examples, tutorials and recipes to help you get started with statsmodels. Each of the examples shown here is made available as an IPython Notebook and as a plain python script on the statsmodels github repository. If you are not comfortable with git, we also encourage users to submit their own examples, tutorials or cool statsmodels tricks to the Examples wiki page. Univariate Kernel Density Estimator. Generalized Linear Models Overview. Using Formulas with GLMs.

2

Developer Page — statsmodels 0.6.1 documentation

http://www.statsmodels.org/stable/dev/index.html

This page explains how you can contribute to the development of. By submitting patches, statistical tests, new models, or examples. Is developed on Github. Submitting a Bug Report. Include a short, self-contained code snippet that reproduces the problem. Specify the statsmodels version used. You can do this with. If the issue looks to involve other dependencies, also include the output of. Making Changes to the Code. One branch. One feature. Each function, class, method, and attribute needs to be documen...

3

Generalized Least Squares — statsmodels 0.6.1 documentation

http://www.statsmodels.org/stable/examples/notebooks/generated/gls.html

Link to Notebook GitHub. The Longley dataset is a time series dataset:. Let's assume that the data is heteroskedastic and that we know the nature of the heteroskedasticity. We can then define. And use it to give us a GLS model. First we will obtain the residuals from an OLS fit. Assume that the error terms follow an AR(1) process with a trend:. Epsilon i = beta 0 rho epsilon {i-1} eta i$. Where $ eta sim N(0, Sigma 2)$. We can use the GLSAR model with one lag, to get to a similar result:. Users/tom.a...

4

Installation — statsmodels 0.6.1 documentation

http://www.statsmodels.org/stable/install.html

To obtain the latest released version of statsmodels using setuptools. Easy install -U statsmodels. Or follow this link to our PyPI page. We do not release very often but the master branch of our source code is usually fine for everyday use. You can get the latest source from our github repository. Or if you have git installed:. Git clone git:/ github.com/statsmodels/statsmodels.git. If you want to keep up to date with the source on github just periodically do:. In the statsmodels directory. The gist of ...

5

0.6 Release — statsmodels 0.6.1 documentation

http://www.statsmodels.org/stable/release/version0.6.html

What’s new in Statsmodels. Release 0.6.1. Statsmodels 0.6.1 is a bugfix release. All users are encouraged to upgrade to 0.6.1. See the list of fixed issues. For specific backported fixes. Release 0.6.0. Statsmodels 0.6.0 is another large release. It is the result of the work of 37 authors over the last year and includes over 1500 commits. It contains many new features, improvements, and bug fixes detailed below. See the list of fixed issues. For specific closed issues. Y age trt base. The Statsmodels LME...

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StatsModels: Statistics in Python — statsmodels 0.6.1 documentation

Welcome to Statsmodels’s Documentation. You can use R-style formulas together with. Data frames to fit your models. Here is a simple example using ordinary least squares:. Fit regression model (using the natural log of one of the regressors). Lottery Literacy np.log(Pop1831). You can also use. Arrays instead of formulas:. Generate artificial data (2 regressors constant). Have a look at. To see available results. Attributes are described in. And results methods have their own docstrings. Information about...

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