Check Yourself Before You Wreck Yourself: Assessing Discrete Choice Models Through Predictive Simulations
A case study in discrete choice model assessment with predictive simulations.
This repository contains the replication data and code for
Brathwaite, Timothy. "Check yourself before you wreck yourself: Assessing
discrete choice models through predictive simulations" arXiv preprint
arXiv:1806.02307 (2018). https://arxiv.org/abs/1806.02307.
├── LICENSE
├── Makefile <- Makefile with commands like `make data` or
│ `make train`
│
├── README.md <- The top-level README for developers using this
│ project.
├── data
│ ├── external <- Data from third party sources.
│ ├── interim <- Intermediate data that has been transformed.
│ ├── processed <- The final, canonical data sets for modeling.
│ └── raw <- The original, immutable data dump.
│
├── docs <- A default Sphinx project; see sphinx-doc.org for
│ details
│
├── models <- Trained and serialized models, model predictions,
│ or model summaries
│
├── notebooks <- Jupyter notebooks. Naming convention is a number
│ (for ordering), the creator's initials, and a
│ short `-` delimited description, e.g.
│ `_01-jqp-initial-data-exploration`
│
├── references <- Data dictionaries, manuals, key reference papers,
│ and all other explanatory materials
│
├── reports <- Generated analysis as HTML, PDF, LaTeX, etc.
│ └── figures <- Generated graphics and figures to be used in
│ reporting
│ └── tables <- LaTex files for tables to be used in reporting
│ └── complete <- LaTex files for the final report and journal
│ submission
│
├── requirements.txt <- The requirements file to reproduce the analysis
│ environment, e.g. generated with
│ `pip freeze > requirements.txt`
│
├── setup.py <- makes project pip installable (pip install -e .)
│ so src can be imported
│
├── src <- Source code for use in this project.
│ ├── __init__.py <- Makes src a Python module
│ │
│ ├── data <- Scripts to download or generate data
│ │ ├── get_car_data.R
│ │ └── convert_car_data_from_wide_to_long.py
│ │
│ ├── features <- Scripts to turn raw data into modeling features
│ │ ├── build_features.py
│ │ └── build_forecast_data.py
│ │
│ ├── models <- Scripts to train models and then use trained
│ │ │ models to make predictions
│ │ ├── predict_model.py
│ │ └── train_model.py
│ │
│ └── visualization <- Scripts to create exploratory and results
│ oriented visualizations
│ └── predictive_viz.py
│
└── tox.ini <- tox settings file; see tox.testrun.org
Project based on the cookiecutter data science project template. #cookiecutterdatascience