1866 search results for "RSTUDIO"

stringr 1.0.0

May 5, 2015
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stringr 1.0.0

I’m very excited to announce the 1.0.0 release of the stringr package. If you haven’t heard of stringr before, it makes string manipulation easier by: Using consistent function and argument names: all functions start with str_, and the first argument is always the input string This makes stringr easier to learn and easy to use

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Introducing Radiant: A shiny interface for R

May 3, 2015
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Radiant is a platform-independent browser-based interface for business analytics in R, based on the Shiny package. Key features Explore: Quickly and easily summarize, visualize, and analyze your data Cross-platform: It runs in a browser on Windows, Mac, and Linux Reproducible: Recreate results at any time and share work with others as a state file or an

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Update to Introduction to programming econometrics with R

May 2, 2015
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This semester I taught a course on applied econometrics with the R programming language. For this, I created a document that I gave to my students and shared online. This is the kind of document I would have liked to read when I first started using R. I already had some programming experience in C and Pascal but this...

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Shiny: Officer Involved Shootings

May 1, 2015
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US Officer Involved Shootings Mar-Apr 2015 with Shiny Now everyone can be a data analyst with RStudio’s Shiny package. Fellow R programmer and Las Vegas import, Steve Wells, has created a R-markdown report that shows off some of the features of this dynamic framework.  Using data derived from the Gun Violence Archive and Google maps, interested users can manipulate this data using...

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rstanmulticore: A cross-platform R package to automatically run RStan MCMC chains in parallel

May 1, 2015
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*** This work has been supported by a grant from the Spencer Foundation (#201400002). The views expressed are those of the author and do not necessarily reflect those of the Spencer Foundation. *** It seems that the heir to WinBUGS is Stan. With Stan, reasonably complex Bayesian models can be expressed in a compact way

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Dockerizing a Shiny App

April 30, 2015
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After a long pause of more than four months, I am finally back to post here. Unfortunately, many commitments prevented me keep posting, but coming back, i changed the deployment (now this blog runs entirely within a docker container with some other cool things I intend to post more forward) and wrote this post. 1. The post

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The First NY R Conference

April 30, 2015
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The First NY R Conference

by Joseph Rickert Last Friday and Saturday the NY R Conference briefly lit up Manhattan's Union Square neighborhood as the center of the R world. You may have caught some of the glow on twitter. Jared Lander, volunteers from the New York Open Statistical Programming Meetup along with the staff at Workbench (the conference venue) set the bar pretty...

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R in Insurance 2015 Conference Programme

April 28, 2015
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R in Insurance 2015 Conference Programme

The programme for the 3rd R in Insurance conference is on-line. The event will take place on 29 June 2015 at the University of Amsterdam. Time to register now. Special thanks to our sponsors, without whom the conference wouldn't be possible: CYBAEA, RS...

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EARL2015 Conference, London – Presenters Announced

April 27, 2015
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EARL2015 Conference, London – Presenters Announced

We are delighted to announce the impressive line up of speakers for September’s London EARL Conference.  The speakers represent industries including Energy, Leisure, Insurance, FCMG, Finance, Market Research, Healthcare and Sport and offer real world examples of the usage and application of … Continue reading →

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Comparing Tree-Based Classification Methods via the Kaggle Otto Competition

April 27, 2015
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Comparing Tree-Based Classification Methods via the Kaggle Otto Competition

In this post, I’m going to be looking at the progressive performance of different tree-based classification methods in R, using the Kaggle Otto Group Product Classification Challenge as an example. This competition challenges participants to correctly classify products into 1 of 9 classes based on data in 93 features. I’ll start with basic decision trees and … Continue reading...

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