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ASAIP Editor's Blog: August, 2017

ASAIP members,

 

I share with you a heavy heart to say that the ASAIP co-founder and leader of astrostatistics, Joseph Hilbe, passed away earlier this year.  Joe was a remarkable man.  His interests and accomplishments had astonishing range.  He earned a Ph.D. in philosophy, worked with Rudolf Carnap and authored texts on logic, serving for decades as a professor of philosophy at University of Hawaii.  In his 40s, he earned a second doctorate in statistics, quickly becoming a leader in industry, academia, scholarly societies and journals.  In his 60s, he turned his energies to astronomy, creating the Astrostatistics Interest Group within the International Statistical Institute (sister organization to the International Astronomical Union) which he developed into the independent International Astrostatistics Association in 2012.  At that time, he joined Penn State in creating the Astrostatistics and Astroinformatics Portal that we are now enjoying. Since 2000, he authored a dozen textbooks in statistics, some reaping awards and multiple editions.  The latest is his posthumous volume Bayesian Models for Astrophysics Data written with Rafael de Souza and Emille Ishida.  Altogether his work on the interface of astronomical research and statistical methodology was pioneering and effective.  Aside from professional achievements, as a young man he was a nationally-ranked track athlete and coach, and later raised a large family with his wife Cheryl.  We at Penn State can also attest that Joe was a wonderfully warm friend.  

 

With Joe’s departure, the ASAIP will continue its current activities, principally providing resources on Recent PapersMeetings, and Jobs.  But it is also time to consider some changes, particularly if requested by leaders of the associated astrostat/info organizations affiliated with the AAS, IAU, ASA, ISI, IEEE, and LSST.  For example, the Forums might be closed down due to inactivity … the Facebook group on astrostatistics is more active.  If you have ideas on how ASAIP can be improved, please let me know so they can be included in our planning.  

 

One of the active areas of the ASAIP Web site are the lists of meetings.  The summer has already witnessed about 50 gatherings relevant to astrostat/info around the world.  Some of these are sessions at large international meetings (AAS, Joint Statistical Meetings, ISI World Statistics Congress, EWASS).  Others are smaller astrostatistics summer schools (Guanajuato MX, Milan IT, University Park PA USA, Preston UK, and Flic En Flac MU) or software training workshops like Python in Astronomy, SciCoder 9, and Hack Day Together.  The year-long SAMSI astrostatistics program ended its principal phase with emphasis on irregular time series, Gaussian Processes regression, uncertainty quantification, and other topics. 

 

In the next few months, we have major meetings like ADASS XXVII in Santiago CL, IAU Symposium #339 on time domain astronomy in Stellenbosch ZA, Astronomical Data Analysis IX in Valencia ES, and Statistical Challenges in 21st Century Cosmology in Valencia ES.   A CosmoStatisitcs COIN program takes place in in Clermont Ferrand FR (several papers have emerged from past years),  Astro Hack Week in Seattle WA USA, and .Astronomy 9 in Cape Town ZA. Astrostatistics and Big Data summer schools will be held in La Serena CL, Taipei TW, Autrans FR, and Madrid ES.  A few astronomers might want to attend the summer school on nonparametric Bayesian methods in Leuven BE, an advanced R summer school in Vorau AT, International Society of Bayesian Analysis World Meeting in Edinburgh UK, American Geophysical Union meeting in New Orleans LA USA,  the Extremely Large Databases and Data Management meeting in Casino de Royat FR, or the IEEE Symposia on Computational Intelligence in Honolulu HI USA.  

 

The Resources tab in ASAIP includes a page on Methodology books for astronomy.  Four volumes were added in 2016-17:   Python for Astronomers: An Introduction to Scientific Computing  by Imad Pasha & Christopher Agostino (2016), Statistics for Astrophysics: Clustering and Classification edited by D. Frail-Burnet & S. Girard (2016 (with R scripts),Practical Bayesian Inference for Physical Scientists by Coryn Bailer-Jones (2017 with R scripts) and Bayesian Models for Astrophysical Data using R, Python, JAGS and Stan by Joseph Hilbe, Rafael de Souza & Emille Ishida (2017).  Also keep an eye on the page Kaggle-like competitions where interesting challenges occasionally appear.  

 

Yours,

Eric Feigelson

edf-at-astro.psu.edu