# Monthly Archives: May 2017

## A Partial Remedy to the Reproducibility Problem

May 31, 2017
By

Several years ago, John Ionnidis jolted the scientific establishment with an article titled, “Why Most Published Research Findings Are False.” He had concerns about inattention to statistical power, multiple inference issues and so on. Most people had already been aware of all this, of course, but that conversation opened the floodgates, and many more issues … Continue reading A...

## U.S. Residential Energy Use: Machine Learning on the RECS Dataset

May 31, 2017
By

Contributed by Thomas Kassel. He is currently enrolled in the NYC Data Science Academy remote bootcamp program taking place from January-May 2017. This post is based The post U.S. Residential Energy Use: Machine Learning on the RECS Dataset appeared first on NYC Data Science Academy Blog.

## Complete Subset Regressions, simple and powerful

May 31, 2017
By
$Complete Subset Regressions, simple and powerful$

By Gabriel Vasconcelos The complete subset regressions (CSR) is a forecasting method proposed by Elliott, Gargano and Timmermann in 2013. It is as very simple but powerful technique. Suppose you have a set of variables and you want to forecast … Continue reading →

## Euler Problem 23: Non-Abundant Sums

May 31, 2017
By

A solution in the R language to Euler Problem 23. Find the sum of all the positive integers which cannot be written as the sum of two abundant numbers. Continue reading → The post Euler Problem 23: Non-Abundant Sums appeared first on The Devil is in the Data.

## Mapping County Unemployment with blscrapeR

May 31, 2017
By

The blscrapeR package makes it easy to produce choropleth maps of various employment and unemployment rates from the Bureau of Labor Statistics (BLS.) It’s easy enough to pull a metric for a certain county. The code below pulls the unemployment rates...

## Calculate Wages and Benefits with blscrapeR

May 31, 2017
By

The most difficult thing about working with BLS data is gaining a clear understanding on what data are available and what they represent. Some of the more popular data sets can be found on the BLS Databases, Tables & Calculations website. The selec...

## Mapping County Unemployment with blscrapeR

May 31, 2017
By

The blscrapeR package makes it easy to produce choropleth maps of various employment and unemployment rates from the Bureau of Labor Statistics (BLS.) It’s easy enough to pull a metric for a certain county. The code below pulls the unemployment rates...

## My new DataCamp course: Forecasting Using R

May 31, 2017
By

For the past few months I’ve been working on a new DataCamp course teaching Forecasting using R. I’m delighted that it is now available for anyone to do. Course blurb Forecasting involves making predictions about the future. It is required in man...

## Calculate Wages and Benefits with blscrapeR

May 31, 2017
By

The most difficult thing about working with BLS data is gaining a clear understanding on what data are available and what they represent. Some of the more popular data sets can be found on the BLS Databases, Tables & Calculations website. The selec...

## Conditional Generative Adversarial Network with MXNet R package

May 31, 2017
By

This tutorial shows how to build and train a Conditional Generative Adversarial Network (CGAN) on MNIST images. How GAN works A Generative Adversarial Model simultaneously trains two models: a generator that learns to output fake samples from an unkn...