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June 2017
Security: the dangers of copying and pasting R code
Most of the time when we stumble across a code snippet online, we often blindly copy and paste it into the R console. I suspect almost everyone does this. After all, what’s the harm? Consider this simple piece of R code that performs simple linear regression # Generate data x = ... [Read more...]
R and Data Science activities in London, June 27th – 29th
Locke Data will be up to some shenanigans of various stripes in the big smoke. We hope to see you at some of them!
June 26th — Monday Introduction to R (Newcastle) I won’t be in London for this but I’ll be doing a day of Introduction to R ... [Read more...]
R and Data Science activities in London, June 27th – 29th
Locke Data will be up to some shenanigans of various stripes in the big smoke. We hope to see you at some of them! June 26th — Monday Introduction to R (Newcastle) I won’t be in London for this but
The post R and Data Science activities in London, June 27... [Read more...]
14 Jobs for R users (2017-05-06) – from all over the world
[social4i size=”large” align=”float-right”] To post your R job on the next post Just visit this link and post a new R job to the R community. You [Read more...]
Unconf projects 3: available, miner, rcheatsheet, ponyexpress
Continuing our series of blog posts (day 1, day 2) this week about unconf 17.
available
Summary: Ever have trouble naming your software package? Find a great name and realize it's already taken on CRAN, or further along in development on GitHub? The available package makes it easy to check for valid, available ...
Statistical inference with the General Social Survey Data
Setup
Load packages
library(ggplot2)
library(dplyr)
library(statsr)
Load data
load("gss.rdata")
Part 1: Data
Background
The General Social Survey (GSS) is a sociological survey used to collect information and keep a historical record of the...
In case you missed it: May 2017 roundup
In case you missed them, here are some articles from May of particular interest to R users. Many interesting presentations recorded at the R/Finance 2017 conference in Chicago are now available to watch. A review of some of the R packages and projects implemented at the 2017 ROpenSci Unconference. An example ... [Read more...]
Package “SentimentAnalysis” released on CRAN
Authors: Stefan Feuerriegel, Nicolas Pröllochs This report introduces sentiment analysis in R and shows how to use our package “SentimentAnalysis”. What is sentiment analysis? Sentiment analysis is a research branch located at the heart of natural language processing (NLP), computational linguistics and text mining. It refers to any measures ... [Read more...]
Manipulate Biological Data Using Biostrings Package Exercises(Part 3)
Bioinformatics is an amalgamation Biology and Computer science.Biological Data is manipulated using Computers and Computer software’s in Bioinformatics. Biological Data includes DNA; RNA & Proteins. DNA & RNA is made of Nucleotide which are our genetic material in which we are coded.Our Structure and Functions are done by protein, ... [Read more...]
Web data acquisition: from database to dataframe for data analysis and visualization (Part 4)
The previous post described how the deeply nested JSON data on fligths were parsed and stored in an R-friendly database structure. However, looking into the data, the information is not yet ready for statistical analysis and visualization and some further processing is necessary before extracting insights and producing nice plots. ...
Unconf projects 2: checkers, gramr, data-packages, exploRingJSON
Following up on Stefanie's recap of unconf 17, we are following up this entire week with summaries of projects developed at the event. We plan to highlight 4-5 projects each day, with detailed posts from a handful of teams to follow.
checkers
Summary: checkers is a framework for reviewing analysis projects. ... [Read more...]
The Many-Faced Future
The future package defines the Future API, which is a unified, generic, friendly API for parallel processing. The Future API follows the principle of write code once and run anywhere - the developer chooses what to parallelize and the user how and wher... [Read more...]
Gradient Boosting – the coolest kid on the machine learning block
Gradient boosting is a technique attracting attention for its prediction speed and accuracy, especially with large and complex data. Don’t just take my word for it, the chart below shows the rapid growth of Google...
anytime 0.3.0
A new version of the anytime package is now on CRAN. It marks the eleventh release since the inaugural version late last summer.
anytime is a very focused package aiming to do just one thing really well: to convert anything in integer, numeric, character, factor, ordered, ... format to either POSIXct ... [Read more...]
Who Survives Riddler Nation?
I analyze the performance of my ABM solution to the Battle for Riddler Nation and properties of strategy submissions using clustering.
Freedman’s paradox
Recently I came across the classical 1983 paper A note on screening regression equations by David Freedman. Freedman shows in an impressive way the dangers of data reuse in statistical analyses. The potentially dangerous scenarios include those where t...
Rediscovering Rd2roxygen
During a lunch with Rob Hyndman and Earo Wang last week in Melbourne, I was surprised to know that there still existed packages that did not use roxygen to write the R documentation (my greatest sympathy to those poor authors), and I was also pleasantly surprised that Rob knew and ... [Read more...]
Freedman’s paradox
Recently I came across the classical 1983 paper A note on screening regression equations by David Freedman. Freedman shows in an impressive way the dangers of data reuse in statistical analyses. The potentially dangerous scenarios include those where t... [Read more...]
The Case Against Seasonal Unit Roots
There are several ways to model seasonality in a time series. Traditionally, trend-cycle decomposition such as the Holt-Winters procedure has been very popular. Also, until today applied researchers often try to account for seasonality by using seasonal dummy variables. But of course, in a stochastic process it seems unreasonable to ...
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