UMR CNRS 7253

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en:cs [2019/06/18 03:47] – tdenoeuxen:cs [2021/08/16 16:13] – tdenoeux
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 **Instructor:** Thierry Denoeux **Instructor:** Thierry Denoeux
  
-Description: This workshop will present the main modern and classical methods of statistical computing, with examples from econometrics. The course will be composed of six chapters structured in two main parts introducing the foundations of statistical computing. Computer projects will be proposed using the R statistical software. +Description: This course will present the main modern and classical methods of statistical computing, with examples from econometrics. The course will be composed of six chapters structured in two main parts introducing the foundations of statistical computing. Computer projects will be proposed using the R statistical software. 
  
 **Program** **Program**
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 **Slides** **Slides**
-  - {{ :en:cs_chapter1_2019.pdf |Continuous optimization}} +  - {{ :en:cs_chapter1_2021.pdf |Continuous optimization}} 
-  - {{ :en:cs_chapter2_2019.pdf |Combinatorial optimization}} + 
-  - {{ :en:cs_chapter3_2019.pdf |EM algorithm}} +
-  - {{ :en:cs_chapter4_2019.pdf |Classical simulation}} +
-  - {{ :en:cs_chapter5_2019.pdf |Markov-Chain Monte Carlo methods}} +
-  - {{ :en:cs_chapter6_2019.pdf |Bootstrapping}}+
    
    
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   - {{:en:continuous_optimization.pdf|Continuous optimization}}    - {{:en:continuous_optimization.pdf|Continuous optimization}} 
-    * {{ :en:continuous_optimization_ex1_2.r.zip |Solution of exercises 1 and 2}} 
-    * {{ :en:continuous_optimization_ex3_4.r.zip |Solution of exercises 3 and 4}} 
   - {{ :en:combinatorial_optimization_project.pdf |Combinatorial optimization}}   - {{ :en:combinatorial_optimization_project.pdf |Combinatorial optimization}}
-    * {{ :en:chapter2_exercises.r.zip |Solution}} 
   - {{ :en:exercises_chapter3.pdf |EM algorithm}}   - {{ :en:exercises_chapter3.pdf |EM algorithm}}
-    * {{ :en:chapter3_exercices1_2.r.zip |Solution of exercises 1 and 2}} 
   - {{ :en:latent_class_regression.pdf |Latent class regression}}   - {{ :en:latent_class_regression.pdf |Latent class regression}}
-    * {{ :en:program_efficiency.r.zip |Solution}} 
   - {{ :en:exercises_chapter4.pdf |Classical simulation}}   - {{ :en:exercises_chapter4.pdf |Classical simulation}}
-    * {{ :en:chapter4_exercise1.r.zip |Solution of exercise 1}} 
   - {{ :en:exercises_chapter5.pdf |MCMC methods}}   - {{ :en:exercises_chapter5.pdf |MCMC methods}}
-    * {{ :en:chapter5_exercises1_2.r.zip |Solution of exercises 1 and 2}} 
   - {{ :en:exercises_chapter6.pdf |Bootstrapping}}   - {{ :en:exercises_chapter6.pdf |Bootstrapping}}
-    * {{ :en:chapter6_exercises.r.zip |Solutions}} 
    
- 
-**Exam** 
- 
-  * {{ :en:exam_2019.pdf |Final exam 2019}} 
  
 **Data** **Data**

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en/cs.txt · Last modified: 2024/03/26 12:05 by tdenoeux
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