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Adventures in the Land of py-stat

Adventures in the Land of py-stat. Wednesday, August 22, 2012. Now that GSOC is over, I'd like to provide a wrap up what I accomplished this summer. In general, I have 4 main features that are tested and have results that match the Matlab/R counterparts. They are:. Inference on descriptive statistics. Inference on Linear Regression. Inference and Estimation of the accelerated failure time model. Inference and estimation of regression with instrumental variables. Here is a bit more of the specifics:.

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Adventures in the Land of py-stat. Wednesday, August 22, 2012. Now that GSOC is over, I'd like to provide a wrap up what I accomplished this summer. In general, I have 4 main features that are tested and have results that match the Matlab/R counterparts. They are:. Inference on descriptive statistics. Inference on Linear Regression. Inference and Estimation of the accelerated failure time model. Inference and estimation of regression with instrumental variables. Here is a bit more of the specifics:.

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7 elci skew

8 regression

9 fitted ci params

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Adventures in the Land of py-stat | landopystat.blogspot.com Reviews

https://landopystat.blogspot.com

Adventures in the Land of py-stat. Wednesday, August 22, 2012. Now that GSOC is over, I'd like to provide a wrap up what I accomplished this summer. In general, I have 4 main features that are tested and have results that match the Matlab/R counterparts. They are:. Inference on descriptive statistics. Inference on Linear Regression. Inference and Estimation of the accelerated failure time model. Inference and estimation of regression with instrumental variables. Here is a bit more of the specifics:.

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landopystat.blogspot.com

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Adventures in the Land of py-stat: Estimating an AFT model

http://www.landopystat.blogspot.com/2012/08/estimating-aft-model.html

Adventures in the Land of py-stat. Tuesday, August 7, 2012. Estimating an AFT model. Estimation of the parametric Accelerated Failure Time (AFT) model is no walk in the park. Much of the research points to two main methods. The first is Koul et al (1981) in which he uses a synthetic data approach; and Stute (1993, 1996) in which the author uses WLS regression. These are often preferred to other estimators due to their computational simplicity. I have looked but haven't been able to find any.

2

Adventures in the Land of py-stat: Winding Down

http://www.landopystat.blogspot.com/2012/08/winding-down.html

Adventures in the Land of py-stat. Sunday, August 19, 2012. GSOC comes to a close tonight at 12:00 midnight and I could not have asked for a more rewarding summer job. I plan on staying active in the statsmodels community and hope to continue contributing empirical likelihood models as well as other models in the indefinite future. A special thanks to Skipper and Josef as well as Ralf for their help this summer. Your advice was invaluable. Subscribe to: Post Comments (Atom). Slight change of plans.

3

Adventures in the Land of py-stat: Midterm Review

http://www.landopystat.blogspot.com/2012/07/midterm-review.html

Adventures in the Land of py-stat. Wednesday, July 11, 2012. To start things off, GSOC has been a 10/10 for me. I enjoy the work I am doing and the downsides are very minimal. Per my proposal, my GSOC project is right on target. Some features I have so far are empirical likelihood hypothesis tests and confidence intervals for:. Regression parameters in a model forced through the origin. I also added some neat plots that I didn't expect to do. Without question, the problem I didn't foresee that has given ...

4

Adventures in the Land of py-stat: Slight change of plans

http://www.landopystat.blogspot.com/2012/08/slight-change-of-plans.html

Adventures in the Land of py-stat. Wednesday, August 8, 2012. Slight change of plans. Just to make it public, I have decided not to implement model selection criteria but instead to implement instrumental variable regression. More to come soon. Subscribe to: Post Comments (Atom). Slight change of plans. Estimating an AFT model. View my complete profile. Awesome Inc. template. Powered by Blogger.

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Adventures in the Land of py-stat: July 2012

http://www.landopystat.blogspot.com/2012_07_01_archive.html

Adventures in the Land of py-stat. Wednesday, July 11, 2012. To start things off, GSOC has been a 10/10 for me. I enjoy the work I am doing and the downsides are very minimal. Per my proposal, my GSOC project is right on target. Some features I have so far are empirical likelihood hypothesis tests and confidence intervals for:. Regression parameters in a model forced through the origin. I also added some neat plots that I didn't expect to do. Without question, the problem I didn't foresee that has given ...

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landopystat.blogspot.com

Adventures in the Land of py-stat

Adventures in the Land of py-stat. Wednesday, August 22, 2012. Now that GSOC is over, I'd like to provide a wrap up what I accomplished this summer. In general, I have 4 main features that are tested and have results that match the Matlab/R counterparts. They are:. Inference on descriptive statistics. Inference on Linear Regression. Inference and Estimation of the accelerated failure time model. Inference and estimation of regression with instrumental variables. Here is a bit more of the specifics:.

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