Blog Archives

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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Using the tuber package to analyse a YouTube channel

December 11, 2017
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Using the tuber package to analyse a YouTube channel

By Gabriel Vasconcelos So I decided to have a quick look at the tuber package to extract YouTube data in R. My cousin is a singer (a hell of a good one) and he has a YouTube channel (dan vasc), … Continue reading →

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A crazy day in the Bitcoin World

November 29, 2017
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A crazy day in the Bitcoin World

By Gabriel Vasconcelos Today, November 29, 2017 was a crazy day in the Bitcoin world and the craziness is still going on as I write this post. The price range was of thousands of Dollars in a few hours. Bitcoins … Continue reading →

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Formal ways to compare forecasting models: Rolling windows

November 8, 2017
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Formal ways to compare forecasting models: Rolling windows

By Gabriel Vasconcelos Overview When working with time-series forecasting we often have to choose between a few potential models and the best way is to test each model in pseudo-out-of-sample estimations. In other words, we simulate a forecasting situation where … Continue reading →

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Writing Julia functions in R with examples

October 17, 2017
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Writing Julia functions in R with examples

By Gabriel Vasconcelos The Julia programming language is growing fast and its efficiency and speed is now well-known. Even-though I think R is the best language for Data Science, sometimes we just need more. Modelling is an important part of … Continue reading →

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Uber assignment with lpSolve

October 13, 2017
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Uber assignment with lpSolve

By Yuri Fonseca In this post we are going to make an Uber assignment simulation and calculate some metrics of waiting time through simulation. Setting Suppose we live in a 100×100 block city where each block takes 1 minute to … Continue reading →

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How Random Forests improve simple Regression Trees?

September 22, 2017
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How Random Forests improve simple Regression Trees?

By Gabriel Vasconcelos Regression Trees In this post I am going to discuss some features of Regression Trees an Random Forests. Regression Trees are know to be very unstable, in other words, a small change in your data may drastically … Continue reading →

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