Blog Archives

Contest: Prizes for Best R User Groups Plotting Code

June 19, 2014
By

by Joseph Rickert For the past year or so we have been plotting the location of R user groups around the world using code (Download RUGS) adapted from a solution that Sandy Muspratt originally posted on Stack Overflow. In last week’s post, we made a modest improvement to our presentation by including a map of Europe. However, R users...

Read more »

Constructing a Continuous Futures Series From Quandl

June 17, 2014
By
Constructing a Continuous Futures Series From Quandl

by Ilya Kipnis In this post, I will demonstrate how to obtain, stitch together, and clean data for backtesting using futures data from Quandl. Quandl was previously introduced in the Revolutions Blog. Functions I will be using can be found in my IK Trading package available on my github page. With backtesting, it’s often times easy to get data...

Read more »

R User Groups June 2014

June 12, 2014
By
R User Groups June 2014

by Joseph Rickert useR! 2014 is just about two weeks away, and I am very much looking forward to meeting R users from around the world. This is just a great time to catch up with old friends, hopefully make some new friends, and talk about R and R user groups. The number of R user groups continues to...

Read more »

Quantitative Finance Applications in R – 6: Constructing a Term Structure of Interest Rates Using R (Part 1)

June 10, 2014
By
Quantitative Finance Applications in R – 6:   Constructing a Term Structure of Interest Rates Using R (Part 1)

by Daniel Hanson Introduction Last time, we used the discretization of a Brownian Motion process with a Monte Carlo method to simulate the returns of a single security, with the (rather strong) assumption of a fixed drift term and fixed volatility. We will return to this topic in a future article, as it relates to basic option pricing methods,...

Read more »

Deep Learning at Stanford

June 5, 2014
By
Deep Learning at Stanford

by Joseph Rickert Last week,I had the opportunity to participate in the Second Academy of Science and Engineering (ASE) Conference on Big Data Science and Computing at Stanford University. Since the conference was held simultaneously with the two other conferences, one on Social Computing and the other on Cyber Security, it was definitely not an R crowd, and not...

Read more »

R / Finance 2014: Packaged Takeaways

May 29, 2014
By
R / Finance 2014: Packaged Takeaways

by Joseph Rickert I was very happy to have been able to attend R / Finance 2014 which wrapped up a couple of weeks ago. In general, the talks were at a very high level of play, some dealing with brand new ideas and many presented at a significant level of technical or mathematical sophistication. Fortunately, most of the...

Read more »

Quick History 2: GLMs, R and large data sets

May 22, 2014
By

by Joseph Rickert In last week’s post, I sketched out the history of Generalized Linear Models and their implementations. In this post I’ll attempt to outline how GLM functions evolved in R to handle large data sets. The first function to make it possible to build GLM models with datasets that are too big to fit into memory was...

Read more »

Ensemble Methods Part 3: Revolution Analytics Big Data Random Forest Function

May 20, 2014
By
Ensemble Methods Part 3: Revolution Analytics Big Data Random Forest Function

by Mike Bowles In two previous posts, A Thumbnail History of Ensemble Methods and Ensemble Packages in R, Mike Bowles — a machine learning expert and serial entrepreneur — laid out a brief history of ensemble methods and described a few of the many implementations in R. In this post Mike takes a detailed look at the Random Forests...

Read more »

Quick History: glm()

May 15, 2014
By

by Joseph Rickert I recently wrote about some R resources that are available for generalized linear models (GLMs). Looking over the material, I was amazed by the amount of effort that is continuing to go into GLMs, both with with respect to new theoretical developments and also in response to practical problems such as the need to deal with...

Read more »

Plotly and rOpenSci: Make ggplots shareable and interactive.

May 13, 2014
By
Plotly and rOpenSci: Make ggplots shareable and interactive.

By Matt Sundquist Plotly's Co-Founder Here at Plotly, we are on a mission to build a platform where data scientists can analyze data, create beautiful graphs and collaborate: like a GitHub for data, where you can share and find plots, data, and code. The benefits are: Plots (including ggplot2 plots) are interactive and drawn with D3 (try zooming, panning,...

Read more »