Archive for applied statistics
celebrating the career of Adrian Raftery
Posted in Books, Mountains, Statistics, Travel, University life with tags ABCDE, Adrian Raftery, applied statistics, Bayesian statistics, computational Bayesian methods, Environmental Statistics, Ireland, JSM 2024, Monte Carlo Statistical Methods, Oregon, Pacific North West, Paris 6, Portland, Seattle, statistical demography, United Nations, University of Washington, USA, UW, Washington State on July 28, 2024 by xi'an
the most important statistical ideas of the past 50 years
Posted in Books, pictures, Statistics, Travel with tags ABC, applied statistics, Bayesian Analysis, Bayesian nonparametrics, Bayesian optimization, big data, Biometrika, bootstrap, divide & conquer, EDA, Helsinki, list, machine learning, reinforcement learning, replication crisis, robustness, statistical computing, theory of statistics on January 10, 2020 by xi'an
Aki and Andrew are celebrating the New Year in advance by composing a list of the most important statistics ideas occurring (roughly) since they were born (or since Fisher died)! Like
- substitution of computing for mathematical analysis (incl. bootstrap)
- fitting a model with a large number of parameters, using some regularization procedure to get stable estimates and good predictions (e.g., Gaussian processes, neural networks, generative adversarial networks, variational autoencoders)
- multilevel or hierarchical modelling (incl. Bayesian inference)
- advances in statistical algorithms for efficient computing (with a long list of innovations since 1970, including ABC!), pointing out that a large fraction was of the divide & conquer flavour (in connection with large—if not necessarily Big—data)
- statistical decision analysis (e.g., Bayesian optimization and reinforcement learning, getting beyond classical experimental design )
- robustness (under partial specification, misspecification or in the M-open world)
- EDA à la Tukey and statistical graphics (and R!)
- causal inference (via counterfactuals)
Now, had I been painfully arm-bent into coming up with such a list, it would have certainly been shorter, for lack of opinion about some of these directions (even the Biometrika deputeditoship has certainly helped in reassessing the popularity of different branches!), and I would have have presumably been biased towards Bayes as well as more mathematical flavours. Hence objecting to the witty comment that “theoretical statistics is the theory of applied statistics”(p.10) and including Ghosal and van der Vaart (2017) as a major reference. Also bemoaning the lack of long-term structure and theoretical support of a branch of the machine-learning literature.
Maybe also more space and analysis could have been spent on “debates remain regarding appropriate use and interpretation of statistical methods” (p.11) in that a major difficulty with the latest in data science is not so much the method(s) as the data on which they are based, which in a large fraction of the cases, is not representative and is poorly if at all corrected for this bias. The “replication crisis” is thus only one (tiny) aspect of the challenge.
postdoc in Bayesian machine learning in Berlin [reposted]
Posted in R, Statistics, Travel, University life with tags applied statistics, Berlin, C/C++, Emmy Noether, German Research Foundation, Germany, Humboldt University of Berlin, Humboldt-Universität zu Berlin, machine learning, Matlab, postdoctoral position, Python, R on December 24, 2019 by xi'an
The working group of Statistics at Humboldt University of Berlin invites applications for one Postdoctoral research fellow (full-time employment, 3 years with extension possible) to contribute to the research on mathematical and statistical aspects of (Bayesian) learning approaches. The research positions are associated with the Emmy Noether group Regression Models beyond the Mean – A Bayesian Approach to Machine Learning and working group of Applied Statistics at the School of Business and Economics at Humboldt-Universität Berlin. Opportunities for own scientific qualification (PhD)/career development are provided, see an overview and further links. The positions are to be filled at the earliest possible date and funded by the German Research Foundation (DFG) within the Emmy Noether programme.
Requirements:
– an outstanding PhD in Statistics, Mathematics, or related field with specialisation in Statistics, Data Science or Mathematics;
– a strong background in at least one of the following fields: mathematical statistics, computational methods, Bayesian statistics, statistical learning, advanced regression modelling;
– a thorough mathematical understanding.
– substantial experience in scientific programming with Matlab, Python, C/C++, R or similar;
– strong interest in developing novel statistical methodology and its applications in various fields such as economics or natural and life sciences;
– a very good communication skills and team experience, proficiency of the written and spoken English language (German is not obligatory).
Opportunities:
We offer the unique environment of young researchers and leading international experts in the fields. The vibrant international network includes established collaborations in Singapore and Australia. The positions offer potential to closely work with several applied sciences. Information about the research profile of the research group and further contact details can be found here. The positions are paid according to the Civil Service rates of the German States “TV-L”, E13 (if suitably qualified).
Applications should include:
– a CV with list of publications
– a motivational statement (at most one page) explaining the applicant’s interest in the announced position as well as their relevant skills and experience
– copies of degrees/university transcripts
– names and email addresses of at least two professors that may provide letters of recommendation directly to the hiring committee Applications should be sent as a single PDF file to: Prof. Dr. Nadja Klein (nadja.klein[at]hu-berlin.de), whom you may also contact for questions concerning this job post. Please indicate “Research Position Emmy Noether”.
Application deadline: 31st of January 2020
HU is seeking to increase the proportion of women in research and teaching, and specifically encourages qualified female scholars to apply. Severely disabled applicants with equivalent qualifications will be given preferential consideration. People with an immigration background are specifically encouraged to apply. Since we will not return your documents, please submit copies in the application only.
SADA’16
Posted in pictures, Statistics, Travel, University life with tags Africa, applied statistics, Bayesian Analysis, Bénin, big data, biostatistics, conference, Cotonou, data analysis, econometrics, Pau, SADA'16, surveys on April 28, 2016 by xi'an
Big Bayes stories in print [and in force]
Posted in Books, Statistics, University life with tags applied statistics, arXiv, Bayes 250, Bayesian statistics, Kerrie Mengersen, Thomas Bayes on May 20, 2014 by xi'an
The special issue of Statistical Science Kerrie Mengersen and I edited over the past three (four?) years is now out in print! Even though many ‘Og readers may have already seen the table of contents, here it is once again. We hope you will enjoy this 100 page long excursion in big Bayesiana. The papers are not freely accessible as “current papers” on the journal website but can yet be found in the “future papers” section. (If a sponsor wants to support turning the papers into open access version, he or she is most welcome to contact us or the IMS!) And, thanks to Larry for reminding me!, available on arXiv. Thanks to all authors, discussants, reviewers and special kudos to Jon Wellner for his constant help and support in putting the special issue together!
- Big Bayes Stories—Foreword
- Bayesian Estimation of Population-Level Trends in Measures of Health Status
- Discussion of “Estimating the Distribution of Dietary Consumption Patterns”
- Contribution M. A. Girolam
- Wonderful Examples, but Let’s not Close Our Eyes
- Discussion
- Reply to the Discussion of “Estimating the Distribution of Dietary Consumption Patterns”
- Response to Discussion by A. H. Welsh on the AF 447 Paper
Xi'an's Og 