Blog Archives

BooST series II: Pricing Optimization

October 1, 2018
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BooST series II: Pricing Optimization

By Gabriel Vasconcelos & Yuri Fonseca Introduction This post is the second of a series of examples of the BooST (Boosting Smooth Trees) model. You can see an introduction to the model here and the first example here. Our objective … Continue reading →

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Growing Objects and Loop Memory Pre-Allocation

August 23, 2018
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Growing Objects and Loop Memory Pre-Allocation

By Thiago Milagres Preallocating Memory This will be a short post about a simple, but very important concept that can drastically increase the speed of poorly written codes. It is very common to see R loops written as follows: This … Continue reading →

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BooST series I: Advantage in Smooth Functions

August 20, 2018
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BooST series I: Advantage in Smooth Functions

By Gabriel Vasconcelos and Yuri Fonseca Introduction This is the first of a series of post on the BooST (Boosting Smooth Trees). If you missed the first post introducing the model click here and if you want to see the … Continue reading →

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BooST (Boosting Smooth Trees) a new Machine Learning Model for Partial Effect Estimation in Nonlinear Regressions

August 14, 2018
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BooST (Boosting Smooth Trees) a new Machine Learning Model for Partial Effect Estimation in Nonlinear Regressions

By Gabriel Vasconcelos and Yuri Fonseca   We are happy to introduce our new machine learning method called Boosting Smooth Trees (BooST) (full article here). This model was a joint work with professors Marcelo Medeiros and Álvaro Veiga. The BooST … Continue reading →

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Introducing the HCmodelSets Package

August 4, 2018
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Introducing the HCmodelSets Package

By Henrique Helfer Hoeltgebaum Introduction I am happy to introduce the package HCmodelSets, which is now available on CRAN. This package implements the methods proposed by Cox, D.R. and Battey, H.S. (2017). In particular it performs the reduction, exploratory and … Continue reading →

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Tuning xgboost in R: Part II

July 28, 2018
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Tuning xgboost in R: Part II

By Gabriel Vasconcelos In this previous post I discussed some of the parameters we have to tune to estimate a boosting model using the xgboost package. In this post I will discuss the two parameters that were left out in … Continue reading →

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Different demand functions and optimal price estimation in R

June 3, 2018
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Different demand functions and optimal price estimation in R

By Yuri Fonseca Demand models In the previous post about pricing optimization (link here), we discussed a little about linear demand and how to estimate optimal prices in that case. In this post we are going to compare three different … Continue reading →

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Tuning xgboost in R: Part I

May 16, 2018
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Tuning xgboost in R: Part I

By Gabriel Vasconcelos Before we begin, I would like to thank Anuj for kindly including our blog in his list of the top40 R blogs! Check out the full list at his page, FeedSpot! Introduction Tuning a Boosting algorithm for … Continue reading →

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Parametric Portfolio Policies

February 11, 2018
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Parametric Portfolio Policies

By Gabriel Vasconcelos Overview There are several ways to do portfolio optimization out there, each with its advantages and disadvantages. We already discussed some techniques here. Today I am going to show another method to perform portfolio optimization that works … Continue reading →

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Direct forecast X Recursive forecast

January 10, 2018
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Direct forecast X Recursive forecast

By Gabriel Vasconcelos When dealing with forecasting models there is an issue that generates a lot of confusion, which is the difference between direct and recursive forecasts. I believe most people are more used to recursive forecasts because they are … Continue reading →

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