Welcome!

Python Authors: Matt Davis, Jyoti Bansal, Pat Romanski, Donald Meyer, Liz McMillan

Blog Feed Post

Quick History: glm()

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 very large data sets. (See packages biglm, ff, ffbase, RevoScaleR for example.) This led me to wonder about the history of the GLM and its implementations. An adequate exploration of this topic would occupy a serious science historian (which I am definitely not) for a considerable amount of time. However, I think even a brief look at what apears to be the main line of the development of the GLM in R provides some insight into how good software influences statistical practice. A convenient place to start is with the 1972 paper Generalized Linear Models by Nelder and Wedderburn This seems to be the first paper  to give the GLM a life of its own.  The authors pulled things together by: grouping the Normal, Poisson, Binomial (probit) and gamma distributions together as members of the exponential family applying maximum likelihood estimation via the iteratively reweighted least squares algorithm to the family introducing the terminology “generalized linear models” suggesting  that this unification would be a pedagogic improvement that would “simplify the teaching of the subject to both specialists and non-specialists” It is clear that the GLM was not “invented” in 1972. But, Nelder and Wedderburn were able to package up statistical knowledge and a tradition of analysis going pretty far back in a way that will forever shape how statisticians think about generalizations of linear models. For a brief, but fairly detailed account of the history of the major developments in the in categorical data analysis, logistic regression and loglinear models in the early 20th century leading up to the GLM see Chapter 10 of Agresti 1996. (One very interesting fact highlighted by Agresti is that the iteratively reweighted least squares algorithm that Nelder and Weddergurn used to fit GLMs is the method that R.A. Fisher introduced in 1935 to for fitting probit models by means of maximum likelihood.) The first generally available software to implement a wide range of GLMs seems to have been the Fortran based GLIM system which was developed by the Royal Statistical Society’s Working Party on Statistical Computing, released in 1974 and developed through 1993. My guess is that GLIM dominated the field for nearly 20 years until it was eclipsed by the growing popularity of the 1991 version of S, and the introduction of PROC GENMOD in version 6.09 of SAS that was released in the 1993 timeframe. (Note that the first edition of the manual for the MatLab Statistics Toolbox also dates from 1993.) In any event, in the 1980s, the GLM became the “go to” statistical tool that it is today. In the chapter on Generalized Linear Models that they contributed to Chambers and Hastie’s landmark 1992 book, Hastie and Pregibon write that “GLMS have become popular over the past 10 years, partly due to the computer package GLIM …” It is dangerous temptation to attribute more to a quotation like this than the authors intended. Nevertheless, I think it does offer some support for the idea that in a field such as statistics, theory shapes the tools and then the shape of the tools exerts some influence on how the theory develops. R’s glm() function was, of course,  modeled on the S implementation, The stats package documentation states: The original R implementation of glm was written by Simon Davies working for Ross Ihaka at the University of Auckland, but has since been extensively re-written by members of the R Core team.The design was inspired by the S function of the same name described in Hastie & Pregibon (1992). I take this to mean that the R implementation of glm() was much more than just a direct port of the S code. glm() has come a long way. It is very likely that only the SAS PROC GENMOD implementation of the GLM has matched R’s glm()in popularity over the past decade. However, SAS’s closed environment has failed to match open-source R’s ability to foster growth and stimulate creativity. The performance, stability and rock solid reliability of glm() has contributed to making GLMs a basic tool both for statisticians and for the new generation of data scientists as well.   How GLM implementations will develop outside of R in the future is not clear at all. Python’s evolving glm implementation appears to be in the GLIM tradition. (The Python documentation references the paper by Green (1984) which, in-turn, references GLIM.) Going back to first principles is always a good idea, however Python's GLM function apparently only supports one parameter exponential families. The Python developers have a long way to go before they can match R's rich functionality.The Julia glm function is clearly being modeled after R and shows much promise. However, recent threads on the julia-stats google group forum indicate that the Julia developers are just now beginning to work on basic glm() functionality. ReferencesAgresti, Alan, An Introduction to Categorical Data Analysis: John Wiley and Sons (1996)Chambers, John M. and Trevor J. Hastie (ed.), Statistical Models In S: Wadsworth & Brooks /Cole (1992)Green, P.J., Iteratively reweighted least squares for maximum likelihood estimation, and some robust and resistant alternatives: Journal of the Royal Statistical Society, Series (1984)McCullagh, P. and J. A. Nelder. Generalized Linear Models: Chapman & Hall (1990)Nelder, J.A and R.W.M. Wedderburn, Generalized Linear Models: K. R. Statist Soc A (1972), 135, part 3, p. 370

Read the original blog entry...

More Stories By David Smith

David Smith is Vice President of Marketing and Community at Revolution Analytics. He has a long history with the R and statistics communities. After graduating with a degree in Statistics from the University of Adelaide, South Australia, he spent four years researching statistical methodology at Lancaster University in the United Kingdom, where he also developed a number of packages for the S-PLUS statistical modeling environment. He continued his association with S-PLUS at Insightful (now TIBCO Spotfire) overseeing the product management of S-PLUS and other statistical and data mining products.<

David smith is the co-author (with Bill Venables) of the popular tutorial manual, An Introduction to R, and one of the originating developers of the ESS: Emacs Speaks Statistics project. Today, he leads marketing for REvolution R, supports R communities worldwide, and is responsible for the Revolutions blog. Prior to joining Revolution Analytics, he served as vice president of product management at Zynchros, Inc. Follow him on twitter at @RevoDavid

@ThingsExpo Stories
The current age of digital transformation means that IT organizations must adapt their toolset to cover all digital experiences, beyond just the end users’. Today’s businesses can no longer focus solely on the digital interactions they manage with employees or customers; they must now contend with non-traditional factors. Whether it's the power of brand to make or break a company, the need to monitor across all locations 24/7, or the ability to proactively resolve issues, companies must adapt to...
The current age of digital transformation means that IT organizations must adapt their toolset to cover all digital experiences, beyond just the end users’. Today’s businesses can no longer focus solely on the digital interactions they manage with employees or customers; they must now contend with non-traditional factors. Whether it's the power of brand to make or break a company, the need to monitor across all locations 24/7, or the ability to proactively resolve issues, companies must adapt to...
Artificial intelligence, machine learning, neural networks. We’re in the midst of a wave of excitement around AI such as hasn’t been seen for a few decades. But those previous periods of inflated expectations led to troughs of disappointment. Will this time be different? Most likely. Applications of AI such as predictive analytics are already decreasing costs and improving reliability of industrial machinery. Furthermore, the funding and research going into AI now comes from a wide range of com...
SYS-CON Events announced today that GrapeUp, the leading provider of rapid product development at the speed of business, will exhibit at SYS-CON's 21st International Cloud Expo®, which will take place October 31-November 2, 2017, at the Santa Clara Convention Center in Santa Clara, CA. Grape Up is a software company, specialized in cloud native application development and professional services related to Cloud Foundry PaaS. With five expert teams that operate in various sectors of the market acr...
In this presentation, Striim CTO and founder Steve Wilkes will discuss practical strategies for counteracting fraud and cyberattacks by leveraging real-time streaming analytics. In his session at @ThingsExpo, Steve Wilkes, Founder and Chief Technology Officer at Striim, will provide a detailed look into leveraging streaming data management to correlate events in real time, and identify potential breaches across IoT and non-IoT systems throughout the enterprise. Strategies for processing massive ...
SYS-CON Events announced today that Ayehu will exhibit at SYS-CON's 21st International Cloud Expo®, which will take place on October 31 - November 2, 2017 at the Santa Clara Convention Center in Santa Clara California. Ayehu provides IT Process Automation & Orchestration solutions for IT and Security professionals to identify and resolve critical incidents and enable rapid containment, eradication, and recovery from cyber security breaches. Ayehu provides customers greater control over IT infras...
Internet of @ThingsExpo, taking place October 31 - November 2, 2017, at the Santa Clara Convention Center in Santa Clara, CA, is co-located with 21st Cloud Expo and will feature technical sessions from a rock star conference faculty and the leading industry players in the world. The Internet of Things (IoT) is the most profound change in personal and enterprise IT since the creation of the Worldwide Web more than 20 years ago. All major researchers estimate there will be tens of billions devic...
SYS-CON Events announced today that MobiDev, a client-oriented software development company, will exhibit at SYS-CON's 21st International Cloud Expo®, which will take place October 31-November 2, 2017, at the Santa Clara Convention Center in Santa Clara, CA. MobiDev is a software company that develops and delivers turn-key mobile apps, websites, web services, and complex software systems for startups and enterprises. Since 2009 it has grown from a small group of passionate engineers and business...
SYS-CON Events announced today that Cloud Academy named "Bronze Sponsor" of 21st International Cloud Expo which will take place October 31 - November 2, 2017 at the Santa Clara Convention Center in Santa Clara, CA. Cloud Academy is the industry’s most innovative, vendor-neutral cloud technology training platform. Cloud Academy provides continuous learning solutions for individuals and enterprise teams for Amazon Web Services, Microsoft Azure, Google Cloud Platform, and the most popular cloud com...
SYS-CON Events announced today that CA Technologies has been named "Platinum Sponsor" of SYS-CON's 21st International Cloud Expo®, which will take place October 31-November 2, 2017, at the Santa Clara Convention Center in Santa Clara, CA. CA Technologies helps customers succeed in a future where every business - from apparel to energy - is being rewritten by software. From planning to development to management to security, CA creates software that fuels transformation for companies in the applic...
SYS-CON Events announced today that IBM has been named “Diamond Sponsor” of SYS-CON's 21st Cloud Expo, which will take place on October 31 through November 2nd 2017 at the Santa Clara Convention Center in Santa Clara, California.
We build IoT infrastructure products - when you have to integrate different devices, different systems and cloud you have to build an application to do that but we eliminate the need to build an application. Our products can integrate any device, any system, any cloud regardless of protocol," explained Peter Jung, Chief Product Officer at Pulzze Systems, in this SYS-CON.tv interview at @ThingsExpo, held November 1-3, 2016, at the Santa Clara Convention Center in Santa Clara, CA
Amazon started as an online bookseller 20 years ago. Since then, it has evolved into a technology juggernaut that has disrupted multiple markets and industries and touches many aspects of our lives. It is a relentless technology and business model innovator driving disruption throughout numerous ecosystems. Amazon’s AWS revenues alone are approaching $16B a year making it one of the largest IT companies in the world. With dominant offerings in Cloud, IoT, eCommerce, Big Data, AI, Digital Assista...
SYS-CON Events announced today that Enzu will exhibit at SYS-CON's 21st Int\ernational Cloud Expo®, which will take place October 31-November 2, 2017, at the Santa Clara Convention Center in Santa Clara, CA. Enzu’s mission is to be the leading provider of enterprise cloud solutions worldwide. Enzu enables online businesses to use its IT infrastructure to their competitive advantage. By offering a suite of proven hosting and management services, Enzu wants companies to focus on the core of their ...
Multiple data types are pouring into IoT deployments. Data is coming in small packages as well as enormous files and data streams of many sizes. Widespread use of mobile devices adds to the total. In this power panel at @ThingsExpo, moderated by Conference Chair Roger Strukhoff, panelists looked at the tools and environments that are being put to use in IoT deployments, as well as the team skills a modern enterprise IT shop needs to keep things running, get a handle on all this data, and deliver...
In his session at @ThingsExpo, Eric Lachapelle, CEO of the Professional Evaluation and Certification Board (PECB), provided an overview of various initiatives to certify the security of connected devices and future trends in ensuring public trust of IoT. Eric Lachapelle is the Chief Executive Officer of the Professional Evaluation and Certification Board (PECB), an international certification body. His role is to help companies and individuals to achieve professional, accredited and worldwide re...
IoT solutions exploit operational data generated by Internet-connected smart “things” for the purpose of gaining operational insight and producing “better outcomes” (for example, create new business models, eliminate unscheduled maintenance, etc.). The explosive proliferation of IoT solutions will result in an exponential growth in the volume of IoT data, precipitating significant Information Governance issues: who owns the IoT data, what are the rights/duties of IoT solutions adopters towards t...
With the introduction of IoT and Smart Living in every aspect of our lives, one question has become relevant: What are the security implications? To answer this, first we have to look and explore the security models of the technologies that IoT is founded upon. In his session at @ThingsExpo, Nevi Kaja, a Research Engineer at Ford Motor Company, discussed some of the security challenges of the IoT infrastructure and related how these aspects impact Smart Living. The material was delivered interac...
With major technology companies and startups seriously embracing Cloud strategies, now is the perfect time to attend 21st Cloud Expo October 31 - November 2, 2017, at the Santa Clara Convention Center, CA, and June 12-14, 2018, at the Javits Center in New York City, NY, and learn what is going on, contribute to the discussions, and ensure that your enterprise is on the right path to Digital Transformation.
No hype cycles or predictions of zillions of things here. IoT is big. You get it. You know your business and have great ideas for a business transformation strategy. What comes next? Time to make it happen. In his session at @ThingsExpo, Jay Mason, Associate Partner at M&S Consulting, presented a step-by-step plan to develop your technology implementation strategy. He discussed the evaluation of communication standards and IoT messaging protocols, data analytics considerations, edge-to-cloud tec...