4350 search results for "git"

R’s Garden of Probability Distributions

March 21, 2013
By
R’s Garden of Probability Distributions

by Joseph Rickert If you type ?Distributions at the R console you get a list of the 21 probability distributions included in the stats package that ships with base R. The same list appears in the Introduction to R Manual on CRAN and in most of the many fine introductory books available for the R language. These are indeed...

Read more »

And so begins English Composition I

March 21, 2013
By
And so begins English Composition I

This week started the English Composition I: Achieving Expertise course (Comer, 2013) that I have been looking forward to. I am not sure yet how long I will last, but I hope to enjoy it as much as I can. Plus, it should help me with my...

Read more »

RserveCLI2, a .net client for Rserve

March 20, 2013
By

RserveCLI is a .net/cli client for Rserve, created by Oliver M. Haynold. Oliver has done a great job with this project. I forked this project to add features, fix bugs, and do some restructuring. I thought it was a significant enough depature to cre...

Read more »

Find the fairest place to meet on the Paris Métro

March 20, 2013
By
Find the fairest place to meet on the Paris Métro

When I lived in Paris years ago, I worked near Gare du Nord, but my friend Jenny lived near République. If we wanted to meet up after work, we'd just meet halfway along the Orange Métro line, around Gare de l'Est. Easy. Since that's within walking distance we wouldn't actually take the Métro, but Métro stations are useful waypoints...

Read more »

GeoCoding,R, and The Rolling Stones – Part 2

March 20, 2013
By
GeoCoding,R, and The Rolling Stones – Part 2

Welcome to Part 2 of the GeoCoding, R, and the Rolling Stones blog. Let’s apply some of the things we learned in Part 1 to a practical real world example. Mapping the Stones – A Real Example The Rolling Stones have toured for many years. You can go to Wikipedia and see information on the

Read more »

GeoCoding,R, and The Rolling Stones – Part 2

March 20, 2013
By
GeoCoding,R, and The Rolling Stones – Part 2

Welcome to Part 2 of the GeoCoding, R, and the Rolling Stones blog. Let’s apply some of the things we learned in Part 1 to a practical real world example. Mapping the Stones – A Real Example The Rolling Stones have toured for many years. You can go to Wikipedia and see information on the

Read more »

GeoCoding, R, and The Rolling Stones – Part 1

March 20, 2013
By
GeoCoding, R, and The Rolling Stones – Part 1

In this article I discuss a general approach for Geocoding a location from within R, processing XML reports, and using R packages to create interactive maps. There are various ways to accomplish this, though using Google’s GeoCoding service is a good place to start. We’ll also talk a bit about the XML package that is

Read more »

GeoCoding, R, and The Rolling Stones – Part 1

March 20, 2013
By
GeoCoding, R, and The Rolling Stones – Part 1

In this article I discuss a general approach for Geocoding a location from within R, processing XML reports, and using R packages to create interactive maps. There are various ways to accomplish this, though using Google’s GeoCoding service is a good place to start. We’ll also talk a bit about the XML package that is

Read more »

Optimal Meeting Point on the Paris Metro

March 20, 2013
By

tl;dr: Play with the app here When you live in Paris, chances are you are (home or work) very close to a metro station, so when you want to meet with some friends, you usually end up picking another metro station as a meeting point. Yet, finding the optimal place to meet can easily become a complex problem considering...

Read more »

Animating neural networks from the nnet package

March 19, 2013
By
Animating neural networks from the nnet package

My research has allowed me to implement techniques for visualizing multivariate models in R and I wanted to share some additional techniques I’ve developed, in addition to my previous post. For example, I think a primary obstacle towards developing a useful neural network model is an under-appreciation of the effects model parameters have on model

Read more »