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  1. Sparse_data_classification Sparse_data_classification Public

    Classification of sparse data. Is it possible to discover the underlying parameters when the data are sparse? I also evaluated the performance of discriminant analysis, nearest neighbors, neural ne…

    R 1

  2. Data-management-with-R-Python-SQL-SAS Data-management-with-R-Python-SQL-SAS Public

    Cleaning data will take 40% of your time. I showed solutions to frequent problems in common platforms. Also discussed web scraping and text mining.

    Jupyter Notebook 1 1

  3. Logistic-to-BLP-model-from-scratch Logistic-to-BLP-model-from-scratch Public

    Random coefficient discrete choice model by Berry Levinsohn and Pakes 1995. Estimates customers' valuation of product features and market power of rival companies without requiring household survey.

    R 1 1

  4. Applied-optimization Applied-optimization Public

    Optimization. Regression using gradient descent. Maximize profit subject to constraints. Example of fitting curves to the unobserved part of the data with economic intuition.

    Jupyter Notebook 2

  5. Causal-inference-with-econometrics-and-ML Causal-inference-with-econometrics-and-ML Public

    I discuss obtaining the reduced form and causal inference in traditional form and machine learning. Treatment effects with machine learning was proposed by Tibshirani, Athey, Friedberg et al. (2019…

    R 2 1

  6. Time-series-autoregressive-error-correction Time-series-autoregressive-error-correction Public

    Examples of vector autoregressive model. I also discussed vector error correction and time series models for forecasting purposes.

    R 1