Miniproject for Modern Regression Methods (MATH-408), EPFL
Authors:
AGNAOU Zineb
BOHDAL Martin
10.7.2021
Files:
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data_import.R: imports the data and modifies the original variables
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EDA.* : exploratory data analysis and visualisation of the data
- EDA.ipynb: R Jupyter notebook with printed outputs
- EDA.html: exported R Jupyter notebook
- EDA.R: script in R without output
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GLM.R: complete GLM analysis
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List_of_models.pdf: list of chosen models using GLM analysis
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GAM_utils.R: module for loading libraries and functions that are used to analyse GAM
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GAM_Modelling.* : modelling using GAM with Poisson, Quasipoisson, Negative Binomial response distributions
- GAM_Modelling.ipynb: R Jupyter notebook with printed outputs
- GAM_Modelling.html: exported R Jupyter notebook
- GAM_Modelling.R: R script without output
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GAM_Analysis-of-models.* : Diagnostics, summaries and analysis of the models
- GAM_Analysis-of-models.ipynb: R Jupyter notebook with printed outputs
- GAM_Analysis-of-models.html: exported R Jupyter notebook
- GAM_Analysis-of-models.R: R script without output
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GAM_predictions.R: predictions for missing (NA) values in the dataset using GAM with Quasipoisson