https://github.com/m-clark/models-by-example

By-hand code for models and algorithms. An update to the 'Miscellaneous-R-Code' repo.
https://github.com/m-clark/models-by-example

algorithms bayesian cox-model expectation-maximization gaussian-processes gradient-descent hamiltonian-monte-carlo lasso linear-regression logistic-regression machine-learning maximum-likelihood-estimation mixed-models neural-network pca penalized-regression ridge-regression rkhs splines zero-inflated

Last synced: 23 days ago
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By-hand code for models and algorithms. An update to the 'Miscellaneous-R-Code' repo.

• Host: GitHub
• URL: https://github.com/m-clark/models-by-example
• Owner: m-clark
• Created: 2020-11-01T15:00:11.000Z (about 4 years ago)
• Default Branch: main
• Last Pushed: 2021-01-28T16:26:30.000Z (almost 4 years ago)
• Last Synced: 2023-08-05T08:24:43.117Z (over 1 year ago)
• Topics: algorithms, bayesian, cox-model, expectation-maximization, gaussian-processes, gradient-descent, hamiltonian-monte-carlo, lasso, linear-regression, logistic-regression, machine-learning, maximum-likelihood-estimation, mixed-models, neural-network, pca, penalized-regression, ridge-regression, rkhs, splines, zero-inflated
• Language: R
• Homepage: https://m-clark.github.io/models-by-example/
• Size: 26.2 MB
• Stars: 58
• Watchers: 3
• Forks: 16
• Open Issues: 0
• Metadata Files:
  • Readme: README.html

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README

        


  

  

  Model Estimation by Example | README.utf8

  

  

  

  

  

  

  

  

  

  

  

  

  

  

  

  

  

  

  


    


      




Model Estimation by Example




Model Estimation by Example





   

      

   





   


      

         

      

   





   


      

         

         

         

      

   





      

    


    


      


        


          


            

          

        


        


          


            



Model Estimation by Example



This is the repo for the document found here, based on the raw code repo- Miscellaneous R Code. The document code has been tidied and may have other improvements relative to the original repo, but remains a conceptual/tutorial.



            


          

        

      


    

  


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