Cookies help us display personalized product recommendations and ensure you have great shopping experience.

By using this site, you agree to the Privacy Policy and Terms of Use.
Accept
SmartData CollectiveSmartData Collective
  • Analytics
    AnalyticsShow More
    sales and data analytics
    How Data Analytics Improves Lead Management and Sales Results
    9 Min Read
    data analytics and truck accident claims
    How Data Analytics Reduces Truck Accidents and Speeds Up Claims
    7 Min Read
    predictive analytics for interior designers
    Interior Designers Boost Profits with Predictive Analytics
    8 Min Read
    image fx (67)
    Improving LinkedIn Ad Strategies with Data Analytics
    9 Min Read
    big data and remote work
    Data Helps Speech-Language Pathologists Deliver Better Results
    6 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: The R-Files: Martyn Plummer
Share
Notification
Font ResizerAa
SmartData CollectiveSmartData Collective
Font ResizerAa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Data Management > Best Practices > The R-Files: Martyn Plummer
AnalyticsBest PracticesR Programming Language

The R-Files: Martyn Plummer

DavidMSmith
DavidMSmith
6 Min Read
SHARE

“The R-Files” is an occasional series from Revolution Analytics, where we profile prominent members of the R Community.

“The R-Files” is an occasional series from Revolution Analytics, where we profile prominent members of the R Community.

R-Files 

More Read

Image
Are You Recruiting Smart? The Application of Big Data in HR
The Evolving Importance of Analytics in Generating Leads through PPC
First Look – KXEN
3 Organizations That Can See the Future with Predictive Analytics
The Data Analytics of Harry Potter
Martyn plummer

Name: Martyn Plummer

Occupation: Statistician at International Agency for Research on Cancer

Nationality: British

Years Using R: 16

Known for: Member of R core group; member of R Journal editorial board

Martyn Plummer is a longtime contributor to the R community and a member of the R core group, which consists of 20 members that help oversee the continued evolution of the project. Plummer also serves on the editorial board of the R Journal, the official journal of the R project. By day, he serves as a Statistician and Epidemiologist at the International Agency for Research on Cancer (IARC), based in Lyon, France.

Plummer, who has been using R since 1995, has developed or contributed to a number of popular packages, including coda for analyzing Markov Chain Monte Carlo output, JAGS, a clone of the popular WinBUGS software Bayesian analysis and Epi, which provides functions for epidemiologists and accompanies an annual course that aims to introduce epidemiologists to R.

He has also incorporated R into his work at IARC, where he works in the Infection and Cancer Epidemiology group. Much of the work of this group is focused on human papillomavirus (HPV), which causes half a million cases of cervical cancer per year worldwide.  Plummer and his colleagues use R (including his own Epi package) to analyze epidemiological studies of HPV infection and try to tease out some aspects of HPV natural history that are difficult to understand without statistical modeling, such as whether different HPV types interact with each other. He also relies heavily on R’s graphical capabilities for visualizing data in scientific publications.

Prior to R, Plummer worked primarily with S+ for analyzing data. He had been working in Cambridge, United Kingdom in the Biostatistics Unit at the Medical Research Council when he was offered a position at the IARC in Lyon. He recalls the transition, and how his new position introduced an entirely different computing environment. Soon after moving, he was introduced to the recently-formed R project by his colleague David Clayton.

“From the beginning, I saw enormous potential in R,” says Plummer. “While I was accustomed to S+, it wasn’t long before I completely switched over to R. It was and continues to be unparalleled in its flexibility in terms of data analysis.”

Plummer also points to R’s extensible nature as one of its defining features. As a modern language, R is able to effectively adapt to the changing nature of data analysis in an era of increasingly large, unstructured data sets. “One of the most important features of R is that it’s built around the data; it’s designed for programming with data, so it can take these developments in stride,” he says.

He went on to describe a recent article in the R journal that analyzed 18 months’ worth of text from the R mailing lists and identified relationships between prominent members of the R community based on the topics they discussed. Plummer cites it as an example of R’s ability to keep up with the ever-changing notion of “data.”

“10 years ago, I would have never called such an amalgamation of text a ‘data set,’” he says. “Today, though, we find ourselves in a situation where we can elicit structure from large and complex data sets and glean meaning from it.”

When asked about how he sees the R project evolving in coming years, Plummer speaks of a delicate yet effective balance. “R manages a difficult equilibrium; it’s partly a frontier for innovation in statistical computing, yet it’s also a stable platform for data analysis. It’s unique in this regard and I don’t see it facing serious competition for quite some time.”

He sees the current situation being maintained at least over the next few years, though one challenge for R users is to navigate the increasing number of contributed packages.  While there’s incredible innovation being done for a diverse range of functions, Plummer says, there are also opportunities for the community as a whole to pool and share their work.

“One of the most important and oft-overlooked values of the R community is its interdisciplinary nature,” he says. “It’s remarkable to be able to collaborate with so many talented people from a diverse range of fields. We’re all statisticians, but statistics has a terrible tendency to fragment by subject matter. R gives us all a common platform and brings us together to encourage innovation.”

TAGGED:leaderleadership
Share This Article
Facebook Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

sales and data analytics
How Data Analytics Improves Lead Management and Sales Results
Analytics Big Data Exclusive
ai in marketing
How AI and Smart Platforms Improve Email Marketing
Artificial Intelligence Exclusive Marketing
AI Document Verification for Legal Firms: Importance & Top Tools
AI Document Verification for Legal Firms: Importance & Top Tools
Artificial Intelligence Exclusive
AI supply chain
AI Tools Are Strengthening Global Supply Chains
Artificial Intelligence Exclusive

Stay Connected

1.2kFollowersLike
33.7kFollowersFollow
222FollowersPin

You Might also Like

Marketing Lessons from the Collapse of Lehman Brothers

9 Min Read
big data improves
Big DataJobsKnowledge ManagementUncategorized

3 Ways Big Data Improves Leadership Within Companies

6 Min Read
Image
Uncategorized

Driving Technology Projects the Right Way

3 Min Read

Credibility & Data?

5 Min Read

SmartData Collective is one of the largest & trusted community covering technical content about Big Data, BI, Cloud, Analytics, Artificial Intelligence, IoT & more.

ai in ecommerce
Artificial Intelligence for eCommerce: A Closer Look
Artificial Intelligence
AI and chatbots
Chatbots and SEO: How Can Chatbots Improve Your SEO Ranking?
Artificial Intelligence Chatbots Exclusive

Quick Link

  • About
  • Contact
  • Privacy
Follow US
© 2008-25 SmartData Collective. All Rights Reserved.
Go to mobile version
Welcome Back!

Sign in to your account

Username or Email Address
Password

Lost your password?