Interview Rob J Hyndman Forecasting Expert #rstats

Here is an interview with Prof Rob J Hyndman who has created many time series forecasting methods and authored books as well as R packages on the same.

Ajay -Describe your journey from being a student of science to a Professor. What were some key turning points along that journey?
 
Rob- I started a science honours degree at the University of Melbourne in 1985. By the end of 1985 I found myself simultaneously working as a statistical consultant (having completed all of one year of statistics courses!). For the next three years I studied mathematics, statistics and computer science at university, and tried to learn whatever I needed to in order to help my growing group of clients. Often we would cover things in classes that I’d already taught myself through my consulting work. That really set the trend for the rest of my career. I’ve always been an academic on the one hand, and a statistical consultant on the other. The consulting work has led me to learn a lot of things that I would not otherwise have come across, and has also encouraged me to focus on research problems that are of direct relevance to the clients I work with.
I never set out to be an academic. In fact, I thought that I would get a job in the business world as soon as I finished my degree. But once I completed the degree, I was offered a position as a statistical consultant within the University of Melbourne, helping researchers in various disciplines and doing some commercial work. After a year, I was getting bored doing only consulting, and I thought it would be interesting to do a PhD. I was lucky enough to be offered a generous scholarship which meant I was paid more to study than to continue working.
Again, I thought that I would probably go and get a job in the business world after I finished my PhD. But I finished it early and my scholarship was going to be cut off once I submitted my thesis. So instead, I offered to teach classes for free at the university and delayed submitting my thesis until the scholarship period ran out. That turned out to be a smart move because the university saw that I was a good teacher, and offered me a lecturing position starting immediately I submitted my thesis. So I sort of fell into an academic career.
I’ve kept up the consulting work part-time because it is interesting, and it gives me a little extra money. But I’ve also stayed an academic because I love the freedom to be able to work on anything that takes my fancy.
Ajay- Describe your upcoming book on Forecasting.
 
Rob- My first textbook on forecasting (with Makridakis and Wheelwright) was written a few years after I finished my PhD. It has been very popular, but it costs a lot of money (about $140 on Amazon). I estimate that I get about $1 for every book sold. The rest goes to the publisher (Wiley) and all they do is print, market and distribute it. I even typeset the whole thing myself and they print directly from the files I provided. It is now about 15 years since the book was written and it badly needs updating. I had a choice of writing a new edition with Wiley or doing something completely new. I decided to do a new one, largely because I didn’t want a publisher to make a lot of money out of students using my hard work.
It seems to me that students try to avoid buying textbooks and will search around looking for suitable online material instead. Often the online material is of very low quality and contains many errors.
As I wasn’t making much money on my textbook, and the facilities now exist to make online publishing very easy, I decided to try a publishing experiment. So my new textbook will be online and completely free. So far it is about 2/3 completed and is available at http://otexts.com/fpp/. I am hoping that my co-author (George Athanasopoulos) and I will finish it off before the end of 2012.
The book is intended to provide a comprehensive introduction to forecasting methods. We don’t attempt to discuss the theory much, but provide enough information for people to use the methods in practice. It is tied to the forecast package in R, and we provide code to show how to use the various forecasting methods.
The idea of online textbooks makes a lot of sense. They are continuously updated so if we find a mistake we fix it immediately. Also, we can add new sections, or update parts of the book, as required rather than waiting for a new edition to come out. We can also add richer content including video, dynamic graphics, etc.
For readers that want a print edition, we will be aiming to produce a print version of the book every year (available via Amazon).
I like the idea so much I’m trying to set up a new publishing platform (otexts.com) to enable other authors to do the same sort of thing. It is taking longer than I would like to make that happen, but probably next year we should have something ready for other authors to use.
Ajay- How can we make textbooks cheaper for students as well as compensate authors fairly
 
Rob- Well free is definitely cheaper, and there are a few businesses trying to make free online textbooks a reality. Apart from my own efforts, http://www.flatworldknowledge.com/ is producing a lot of free textbooks. And textbookrevolution.org is another great resource.
With otexts.com, we will compensate authors in two ways. First, the print versions of a book will be sold (although at a vastly cheaper rate than other commercial publishers). The royalties on print sales will be split 50/50 with the authors. Second, we plan to have some features of each book available for subscription only (e.g., solutions to exercises, some multimedia content, etc.). Again, the subscription fees will be split 50/50 with the authors.
Ajay- Suppose a person who used to use forecasting software from another company decides to switch to R. How easy and lucid do you think the current documentation on R website for business analytics practitioners such as these – in the corporate world.
 
Rob- The documentation on the R website is not very good for newcomers, but there are a lot of other R resources now available. One of the best introductions is Matloff’s “The Art of R Programming”. Provided someone has done some programming before (e.g., VBA, python or java), learning R is a breeze. The people who have trouble are those who have only ever used menu interfaces such as Excel. Then they are not only learning R, but learning to think about computing in a different way from what they are used to, and that can be tricky. However, it is well worth it. Once you know how to code, you can do so much more.  I wish some basic programming was part of every business and statistics degree.
If you are working in a particular area, then it is often best to find a book that uses R in that discipline. For example, if you want to do forecasting, you can use my book (otexts.com/fpp/). Or if you are using R for data visualization, get hold of Hadley Wickham’s ggplot2 book.
Ajay- In a long and storied career- What is the best forecast you ever made ? and the worst?
 
 Rob- Actually, my best work is not so much in making forecasts as in developing new forecasting methodology. I’m very proud of my forecasting models for electricity demand which are now used for all long-term planning of electricity capacity in Australia (see  http://robjhyndman.com/papers/peak-electricity-demand/  for the details). Also, my methods for population forecasting (http://robjhyndman.com/papers/stochastic-population-forecasts/ ) are pretty good (in my opinion!). These methods are now used by some national governments (but not Australia!) for their official population forecasts.
Of course, I’ve made some bad forecasts, but usually when I’ve tried to do more than is reasonable given the available data. One of my earliest consulting jobs involved forecasting the sales for a large car manufacturer. They wanted forecasts for the next fifteen years using less than ten years of historical data. I should have refused as it is unreasonable to forecast that far ahead using so little data. But I was young and naive and wanted the work. So I did the forecasts, and they were clearly outside the company’s (reasonable) expectations, and they then refused to pay me. Lesson learned. It’s better to refuse work than do it poorly.

Probably the biggest impact I’ve had is in helping the Australian government forecast the national health budget. In 2001 and 2002, they had underestimated health expenditure by nearly $1 billion in each year which is a lot of money to have to find, even for a national government. I was invited to assist them in developing a new forecasting method, which I did. The new method has forecast errors of the order of plus or minus $50 million which is much more manageable. The method I developed for them was the basis of the ETS models discussed in my 2008 book on exponential smoothing (www.exponentialsmoothing.net)

. And now anyone can use the method with the ets() function in the forecast package for R.
About-
Rob J Hyndman is Pro­fessor of Stat­ist­ics in the Depart­ment of Eco­no­met­rics and Busi­ness Stat­ist­ics at Mon­ash Uni­ver­sity and Dir­ector of the Mon­ash Uni­ver­sity Busi­ness & Eco­nomic Fore­cast­ing Unit. He is also Editor-in-Chief of the Inter­na­tional Journal of Fore­cast­ing and a Dir­ector of the Inter­na­tional Insti­tute of Fore­casters. Rob is the author of over 100 research papers in stat­ist­ical sci­ence. In 2007, he received the Moran medal from the Aus­tralian Academy of Sci­ence for his con­tri­bu­tions to stat­ist­ical research, espe­cially in the area of stat­ist­ical fore­cast­ing. For 25 years, Rob has main­tained an act­ive con­sult­ing prac­tice, assist­ing hun­dreds of com­pan­ies and organ­iz­a­tions. His recent con­sult­ing work has involved fore­cast­ing elec­tri­city demand, tour­ism demand, the Aus­tralian gov­ern­ment health budget and case volume at a US call centre.

What is a White Paper?

Christine and Jimmy Wales
Image via Wikipedia

As per Jimmy Wales and his merry band at Wiki (pedia not leaky-ah)- The emphasis is mine

What is the best white paper you have read in the past 15 years.

Categories are-

  • Business benefits: Makes a business case for a certain technology or methodology.
  • Technical: Describes how a certain technology works.
  • Hybrid: Combines business benefits with technical details in a single document.
  • Policy: Makes a case for a certain political solution to a societal or economic challenge.
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white paper is an authoritative report or guide that helps solve a problem. White papers are used to educate readers and help people make decisions, and are often requested and used in politics, policy, business, and technical fields. In commercial use, the term has also come to refer to documents used by businesses as a marketing or sales tool. Policy makers frequently request white papers from universities or academic personnel to inform policy developments with expert opinions or relevant research.

Government white papers

In the Commonwealth of Nations, “white paper” is an informal name for a parliamentary paper enunciating government policy; in the United Kingdom these are mostly issued as “Command papers“. White papers are issued by the government and lay out policy, or proposed action, on a topic of current concern. Although a white paper may on occasion be a consultation as to the details of new legislation, it does signify a clear intention on the part of a government to pass new law. White Papers are a “…. tool of participatory democracy … not [an] unalterable policy commitment.[1] “White Papers have tried to perform the dual role of presenting firm government policies while at the same time inviting opinions upon them.” [2]

In Canada, a white paper “is considered to be a policy document, approved by Cabinet, tabled in the House of Commons and made available to the general public.”[3] A Canadian author notes that the “provision of policy information through the use of white and green papers can help to create an awareness of policy issues among parliamentarians and the public and to encourage an exchange of information and analysis. They can also serve as educational techniques”.[4]

“White Papers are used as a means of presenting government policy preferences prior to the introduction of legislation”; as such, the “publication of a White Paper serves to test the climate of public opinion regarding a controversial policy issue and enables the government to gauge its probable impact”.[5]

By contrast, green papers, which are issued much more frequently, are more open ended. These green papers, also known as consultation documents, may merely propose a strategy to be implemented in the details of other legislation or they may set out proposals on which the government wishes to obtain public views and opinion.

White papers published by the European Commission are documents containing proposals for European Union action in a specific area. They sometimes follow a green paper released to launch a public consultation process.

For examples see the following:

 Commercial white papers

Since the early 1990s, the term white paper has also come to refer to documents used by businesses and so-called think tanks as marketing or sales tools. White papers of this sort argue that the benefits of a particular technologyproduct or policy are superior for solving a specific problem.

These types of white papers are almost always marketing communications documents designed to promote a specific company’s or group’s solutions or products. As a marketing tool, these papers will highlight information favorable to the company authorizing or sponsoring the paper. Such white papers are often used to generate sales leads, establish thought leadership, make a business case, or to educate customers or voters.

There are four main types of commercial white papers:

  • Business benefits: Makes a business case for a certain technology or methodology.
  • Technical: Describes how a certain technology works.
  • Hybrid: Combines business benefits with technical details in a single document.
  • Policy: Makes a case for a certain political solution to a societal or economic challenge.

Resources

  • Stelzner, Michael (2007). Writing White Papers: How to capture readers and keep them engaged. Poway, California: WhitePaperSource Publishing. pp. 214. ISBN 9780977716937.
  • Bly, Robert W. (2006). The White Paper Marketing Handbook. Florence, Kentucky: South-Western Educational Publishing. pp. 256. ISBN 9780324300826.
  • Kantor, Jonathan (2009). Crafting White Paper 2.0: Designing Information for Today’s Time and Attention Challenged Business Reader. Denver,Colorado: Lulu Publishing. pp. 167.ISBN 9780557163243.

Data Visualization: Central Banks

Iron Ore Company of Canada
Image via Wikipedia

Trying to compare the transparency of central banks via the data visualization of two very different central banks.

One is Reserve Bank of India and the other is Federal Reserve Bank of New York

Here are some points-

1) The federal bank gives you a huge clutter of charts to choose from and sometimes gives you very difficult to understand charts.

see http://www.newyorkfed.org/research/global_economy/usecon_charts.html

and http://www.newyorkfed.org/research/directors_charts/us18chart.pdf

us18chart

2) The Reserve bank of India choose Business Objects and gives you a proper drilldown kind  of  graph and tables. ( thats a lot of heavy metal and iron ore China needs from India 😉 😉

Foreign Trade – Export      Time-line: ALL

TIME LINE COUNTRY COMMODITY AMOUNT (US $ MILLION) EXPORT QUANTITY
2010:07 (JUL) – P China IRON ORE (Units: TON) 205.06 1878456
2010:06 (JUN) – P China IRON ORE (Units: TON) 427.68 6808528
2010:05 (MAY) – P China IRON ORE (Units: TON) 550.67 5290450
2010:04 (APR) – P China IRON ORE (Units: TON) 922.46 9931500
2010:03 (MAR) – P China IRON ORE (Units: TON) 829.75 13177672
2010:02 (FEB) – P China IRON ORE (Units: TON) 706.04 10141259
2010:01 (JAN) – P China IRON ORE (Units: TON) 577.13 8498784
2009:12 (DEC) – P China IRON ORE (Units: TON) 545.68 9264544
2009:11 (NOV) – P China IRON ORE (Units: TON) 508.17 9509213
2009:10 (OCT) – P China IRON ORE (Units: TON) 422.6 7691652
2009:09 (SEP) – P China IRON ORE (Units: TON) 278.04 4577943
2009:08 (AUG) – P China IRON ORE (Units: TON) 276.96 4371847
2009:07 (JUL) China IRON ORE (Units: TON) 266.11 4642237
2009:06 (JUN) China IRON ORE (Units: TON) 241.08 4584354

Source : DGCI & S, Ministry of Commerce & Industry, GoI

 

You can see the screenshots of the various visualization tools of the New York Fed Reserve Bank and Indian Reserve Bank- if the US Fed is serious about cutting the debt maybe it should start publishing better visuals

An Introduction to Data Mining-online book

I was reading David Smith’s blog http://blog.revolutionanalytics.com/

where he mentioned this interview of Norman Nie, at TDWI

http://tdwi.org/Articles/2010/11/17/R-101.aspx?Page=2

where I saw this link (its great if you want to study Data Mining btw)

http://www.kdnuggets.com/education/usa-canada.html

and I c/liked the U Toronto link

http://chem-eng.utoronto.ca/~datamining/

Best of All- I really liked this online book created by Professor S. Sayad

Its succinct and beautiful and describes all of the Data Mining you want to read in one Map (actually 4 images painstakingly assembled with perfection)

The best thing is- in the original map- even the sub items are click-able for specifics like Pie Chart and Stacked Column chart are not in one simple drop down like Charts- but rather by nature of the kind of variables that lead to these charts. For doing that- you would need to go to the site itself- ( see http://chem-eng.utoronto.ca/~datamining/dmc/categorical_variables.htm

vs

http://chem-eng.utoronto.ca/~datamining/dmc/categorical_numerical.htm

Again- there is no mention of the data visualization software used to create the images but I think I can take a hint from the Software Page which says software used are-

Software

See it on your own-online book (c)Professor S. Sayad

Really good DIY tutorial

http://chem-eng.utoronto.ca/~datamining/dmc/data_mining_map.htm

The Gospel as per WikiLeaks

Logo used by Wikileaks
Image via Wikipedia

– First Assume Nothing-

I would be very surprised if 260,000 documents and not even one was a counter-intelligence dis information move. Why was ALL the information stored in one place- maybe Wikileaks would leak the launch codes of the missiles next.

One more data visualization for Tableau– R watchers can not how jjplot by Facebook Analytics and Tableau are replacing GGPLOT 2 as visualization standards- (GGPLOT 2 needs a better GUI maybe using pyqt than the Deducer currently- maybe they can create GGPLOT extensions for Red R yet)

and yes stranger stupid things have happened in diplomacy and intelligence (like India exploding the nuclear bomb on exactly the same date and same place —-surprising CIA, but we are supposed to be on the same side atleast for the next decade) but it would be wrong not to cross reference the cables with the some verification.

Tableau gives great data viz though, but I dont think all 260,000 cables are valid data points (and boy they must really be regretting creating the internet at DARPA and DoD- but you can always blame Al Gore for that)