# Tag Archives: R blog

## Treating your data: The old school vs tidyverse modern tools

By Gabriel Vasconcelos When I first started using R there was no such thing as the tidyverse. Although some of the tidyverse packages were available independently, I learned to treat my data mostly using brute force combining pieces of information … Continue reading

## The package hdm for double selection inference with a simple example

By Gabriel Vasconcelos In a late post I discussed the Double Selection (DS), a procedure for inference after selecting controls. I showed an example of the consequences of ignoring the variable selection step discussed in an article by Belloni, Chernozhukov … Continue reading

## Counterfactual estimation on nonstationary data, be careful!!!

By Gabriel Vasconcelos In a recent paper, which can be downloaded here, Carvalho, Masini and Medeiros show that estimating counterfactuals in a non-stationary framework (when I say non-stationary it means integrated) is a tricky task. It is intuitive that the … Continue reading

## ArCo Package v 0.2 is on

The ArCo package 0.2 is now available on CRAN. The functions are now more user friendly. The new features are: Default function for estimation if the user does not inform the functions fn and p.fn. The default model is Ordinary … Continue reading

## Dealing with S3 methods in R with a simple example

By Gabriel Vasconcelos S3 objects R has three object systems: S3, S4 and RC. S3 is by far the easiest to work with and it can make you codes much understandable and organized, especially if you are working on a … Continue reading

## Cross-Fitting Double Machine Learning estimator

By Gabriel Vasconcelos Motivation In a late post I talked about inference after model selection showing that a simple double selection procedure is enough to solve the problem. In this post I’m going to talk about a generalization of the … Continue reading

## Online portfolio allocation with a very simple algorithm

By Yuri Resende Today we will use an online convex optimization technique to build a very simple algorithm for portfolio allocation. Of course this is just an illustrative post and we are going to make some simplifying assumptions. The … Continue reading