Case study on regularisation methods for statistics and machine learning
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Updated
Jun 3, 2019 - R
Case study on regularisation methods for statistics and machine learning
Repository for my Master's thesis comparing volatility models.
Penalized precision matrix estimation
Archived repo - This R Package is not developed anymore (only maintenance). It was replaced by R package rchemo
Analysis of Influencing Factors Leading to Suicidal Actions via Linear Regression and Regularization Methods
Ejercicio de regresiones por distintos métodos (Mejor Selección de Conjuntos, Selección de pasos hacia adelante, Ridge, LASSO, Elastic Net, Componentes Principales, Mínimos Cuadrados Parciales, etc.)
Personal R Package
Comparing the different types of Regression
Post-estimation Shrinkage in Full and Selected Linear Regression Models in Low-Dimensional Data Revisited
Supervised learning and unsupervised in R, with a focus on regression and classification methods.
A repository created to explore and understand Statistics through coding.
Elastic Net, Lasso and Ridge models can be analyzed by the formula format.
R packages which implements most known linear regression model: pls, OLS, ridge, lasso, LAR, principal components regression...
Penalized precision matrix estimation via ADMM
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