Pinned Repositories
aggreating_predictions_sklearn
# Objectives * Create a training function that train the model many time and store the results. * Create a function that collect previous trained model and provide predictions. * I want to do it in parallel using joblib [this library is used to parallelize in Sklearn]
BERTopic
Leveraging BERT and c-TF-IDF to create easily interpretable topics.
covid_forecast
Forecast and Predictions Techniques applied to COVID / Coronavirus
different_notebooks
I put here some notebook I have used to research different topics.
diversity_experiements
This is just to learn about diversity metrics in python.
factor_analyzer
A Python module to perform exploratory factor analysis.
ParallelTextProcessing
I would like to process text in the most parallel possible way
reliabiliPy
Implementation in Python of the reliability measures such as Omega.
SCSL
Synthetic Control with Statistical Learning
Smolyak
Smolyak Method for Solving Dynamic Economic Models: Lagrange Interpolation, Anisotropic Grid and Adaptive Domain (with Kenneth L. Judd, Lilia Maliar and Serguei Maliar). Journal of Economic Dynamics & Control 44 (2014) 92–123. First, we propose a more effcient implementation of the Smolyak method for interpolation, namely, we show how to avoid costly evaluations of repeated basis functions in the conventional Smolyak formula. Second, we extend the Smolyak method to include anisotropic constructions; this allows us to target higher quality of approximation in some dimensions than in others. Third, we show how to effectively adapt the Smolyak hypercube to a solution domain of a given economic model. Finally, we advocate the use of low-cost fixed-point iteration, instead of conventional time iteration. In the context of one- and multi-agent growth models, we find that the proposed techniques lead to substantial increases in accuracy and speed of a Smolyak-based projection method for solving dynamic economic models. JEL classif ication : C63, C68 Key Words : Smolyak method; sparse grid; adaptive domain; projection; anisotropic grid; collocation; high-dimensional problem
rafaelvalero's Repositories
rafaelvalero/reliabiliPy
Implementation in Python of the reliability measures such as Omega.
rafaelvalero/ParallelTextProcessing
I would like to process text in the most parallel possible way
rafaelvalero/different_notebooks
I put here some notebook I have used to research different topics.
rafaelvalero/Smolyak
Smolyak Method for Solving Dynamic Economic Models: Lagrange Interpolation, Anisotropic Grid and Adaptive Domain (with Kenneth L. Judd, Lilia Maliar and Serguei Maliar). Journal of Economic Dynamics & Control 44 (2014) 92–123. First, we propose a more effcient implementation of the Smolyak method for interpolation, namely, we show how to avoid costly evaluations of repeated basis functions in the conventional Smolyak formula. Second, we extend the Smolyak method to include anisotropic constructions; this allows us to target higher quality of approximation in some dimensions than in others. Third, we show how to effectively adapt the Smolyak hypercube to a solution domain of a given economic model. Finally, we advocate the use of low-cost fixed-point iteration, instead of conventional time iteration. In the context of one- and multi-agent growth models, we find that the proposed techniques lead to substantial increases in accuracy and speed of a Smolyak-based projection method for solving dynamic economic models. JEL classif ication : C63, C68 Key Words : Smolyak method; sparse grid; adaptive domain; projection; anisotropic grid; collocation; high-dimensional problem
rafaelvalero/covid_forecast
Forecast and Predictions Techniques applied to COVID / Coronavirus
rafaelvalero/SCSL
Synthetic Control with Statistical Learning
rafaelvalero/aggreating_predictions_sklearn
# Objectives * Create a training function that train the model many time and store the results. * Create a function that collect previous trained model and provide predictions. * I want to do it in parallel using joblib [this library is used to parallelize in Sklearn]
rafaelvalero/BERTopic
Leveraging BERT and c-TF-IDF to create easily interpretable topics.
rafaelvalero/diversity_experiements
This is just to learn about diversity metrics in python.
rafaelvalero/factor_analyzer
A Python module to perform exploratory factor analysis.
rafaelvalero/forecastcovid
Forecast new cases and deaths by day and country
rafaelvalero/grpc_data_functions_experiements
rafaelvalero/how_to_test_in_python
I want to have a little cheatsheet and overview for testing procedures. I focus in two procedures Doctest and Unittest.
rafaelvalero/module_packages
Tutorial about classes, modules and packages
rafaelvalero/pingouin
Statistical package in Python based on Pandas
rafaelvalero/playing_flex_dashboard_shiny
R Shiny Flex Dashboard Interactive Data Visualization
rafaelvalero/python_from_commandline
How to use funtions from the command line. Pick up variables from the commandline.
rafaelvalero/qs-python-samples
Examples of integrating Qlik Sense and Python
rafaelvalero/Smolyak-1
Efficient implementations of Smolyak's algorithm for function approxmation in Python and Julia.
rafaelvalero/sparsegrid
Smolyak sparse grid interpolation sandbox