Statistics Journal Club

All masters students, PhD students, and employees are invited.
Meetings - every other week: to be scheduled
Organizer: Radek Poleski (email: rpoleski@...)

Planned meetings

See below for list of past meetings.
Date and speakerPaper/Topic
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Available papers and topics - choose your favorite and let me know when you want to present.

Some of the papers are long, you may choose to present only part of the paper in such cases.

PaperTitle/topicNotes
Perren, Vázquez and Piatti 2015NEW - "ASteCA: Automated Stellar Cluster Analysis"densities of clusters analyzed
Weigel, Schawinski and Bruderer 2016NEW - "Stellar mass functions: methods, systematics and results for the local Universe"STY maximum likelihood technique, SWML non-parametric maximum likelihood, and 1/Vmax; paper is relatively long
Rojas-Arriagada et al. 2020NEW - "How many components? Quantifying the complexity of the metallicity distribution in the Milky Way bulge with APOGEE"Gaussian mixture model and non-negative matrix factorization decomposition
Camacho, Faria and Viana 2023NEW - "Modelling stellar activity with Gaussian process regression networks"Gaussian processes and other methods
Karamanis et al. 2022NEW - "Accelerating astronomical and cosmological inference with preconditioned Monte Carlo"a novel approach to MCMC; code at https://github.com/minaskar/pocomc
Foreman-Mackey, Agol, Ambikasaran and Angus 2017"Fast and Scalable Gaussian Process Modeling with Applications to Astronomical Time Series"see also https://github.com/dfm/celerite; more advanced version was already presented by M. Mróz
Tsutomou et al. 2022"High Dimensional Statistical Analysis and its Application to ALMA Map of NGC 253"noise-reduction principal component analysis (NRPCA) and regularized principal component analysis (RPCA) used; suggested by Kasia Małek
Bryan et al. 2007"Mapping the Cosmological Confidence Ball Surface"
Importance samplingThe method is very important for speeding-up simulations. Description of the method can be found on-line, or in resources suggested by RP. It would be good to show simple working example.
Speagle 2019"A Conceptual Introduction to Markov Chain Monte Carlo Methods"Other concepts are also discussed: importance sampling, effective sample size, approximating posterior integrals with grids
Vitale 2020"One, No One, and One Hundred Thousand -- Inferring the properties of a population in presence of selection effects"Pedagogical introduction to hierarchical Bayesian inference in presence of selection effects; gravitational waves as an example
Hogg and Forman-Mackey 2017"Data analysis recipes: Using Markov chain Monte Carlo"Good MCMC introduction that has problems to be solved by the reader; discusses convergence, parametrizations etc.
LIGO and Virgo 2020"Population Properties of Compact Objects from the Second LIGO-Virgo Gravitational-Wave Transient Catalog"gravitational waves - statistical analysis of O3 run that considers a few different models
Student projectStudent can present what statistical analysis they work on, even if it's not finished. It's likely that other participants will give useful suggestions
Hsu, Ford, et al. 2018"Improving the Accuracy of Planet Occurrence Rates from Kepler Using Approximate Bayesian Computation"
Schwarzenberg-Czerny 1996"An astronomer's guide to period searching"short
probability distributions used for priorsdiscussion of different probability distributions that are used for priors: beta, Jeffreys, modified Jeffreys etc.
Scargle et al. 2013" Studies in Astronomical Time Series Analysis. VI. Bayesian Block Representations"completely new method
Zechmeister and Kurster 2009"The generalised Lomb-Scargle periodogram. A new formalism for the floating-mean and Keplerian periodograms"
Curran 2014"Monte Carlo error analyses of Spearman's rank test"short one

Past meetings

Date and speakerPaper/TopicLinks
25.05.2023, D. SkowronRaphael Oliviera researchslides
18.05.2023, P. IwanekIwanek et al. 2023 "A Three-dimensional Map of the Milky Way Using 66,000 Mira Variable Stars"slides
20.04.2023, K. IłkiewiczGRAVITY Collaboration 2022 "Deep images of the Galactic center with GRAVITY"slides
6.04.2023, P. SzewczykTekatsy et al. 2023 "What neutron stars tell about the hadron-quark phase transition: a Bayesian study"slides
23.03.2023, P. MrózGraham et al. 2013 "Using conditional entropy to identify periodicity"
9.03.2023, R. PoleskiLuri et al. 2018 "Gaia Data Release 2. Using Gaia parallaxes"slides
24.01.2023, M. MrózGordon, Agol and Foreman-Mackey 2020 "A Fast, Two-dimensional Gaussian Process Method Based on Celerite: Applications to Transiting Exoplanet Discovery and Characterization"slides
20.12.2022, J. SkowronHogg, Bovy and Lang 2010 "Data analysis recipes: Fitting a model to data" - part 2slides
6.12.2022, J. SkowronHogg, Bovy and Lang 2010 "Data analysis recipes: Fitting a model to data" - part 1slides
22.11.2022, M. Ban Koshimoto and Bennett 2020 "Evidence of Systematic Errors in Spitzer Microlens Parallax Measurements"slides
8.11.2022, R. PoleskiHawkins et al. 2017 "Red clump stars and Gaia: calibration of the standard candle using a hierarchical probabilistic model"slides
21.10.2022, J. SkowronIntroduction to MCMC
9.06.2022, M. KiragaSalvato et al. 2018 "Finding counterparts for all-sky X-ray surveys with NWAY: a Bayesian algorithm for cross-matching multiple catalogues"slides
19.05.2022, M. GromadzkiKuhn and Feigelson 2017 "Mixture Models in Astronomy"slides
5.05.2022, K. IłkiewiczFrancis and Wills 1999 "Introduction to Principal Components Analysis"slides
21.04.2022, M. BanUdalski et al. 2018 "OGLE-2017-BLG-1434Lb: Eighth q<1e-4 Mass-Ratio Microlens Planet Confirms Turnover in Planet Mass-Ratio Function"slides
31.03.2022, M. RatajczakSchwarzenberg-Czerny 1989 "On the advantage of using analysis of variance for period search."slides
17.03.2022, R. PoleskiForeman-Mackey, Hogg and Morton 2014 "Exoplanet Population Inference and the Abundance of Earth Analogs from Noisy, Incomplete Catalogs"slides
3.03.2022, P. MrózHogg, Myers, and Bovy 2010 "Inferring the Eccentricity Distribution"notes
11.01.2022, M. JabłońskaAndrae 2010 "Error estimation in astronomy: A guide"slides, github code
14.12.2021, P. SzewczykHogg 2008 "Data analysis recipes: Choosing the binning for a histogram"slides, code
30.11.2021, K. KruszyńskaBailer-Jones et al. 2021 " Estimating Distances from Parallaxes. V. Geometric and Photogeometric Distances to 1.47 Billion Stars in Gaia Early Data Release 3"slides
16.11.2021, J. SkowronIntroduction to MCMC - part 3
9.11.2021, J. SkowronIntroduction to MCMC - part 2
26.10.2021, J. SkowronIntroduction to MCMC - part 1
11.6.2021, D. SkowronVanderPlas and Ivezic 2015 "Periodograms for Multiband Astronomical Time Series"slides
21.5.2021, M. KiragaGould 2013 "The Most Precise Extra-Galactic Black-Hole Mass Measurement"slides
14.5.2021, J. SkowronUltraNest package - based on Buchner (2021) and Buchner (2021)slides
23.4.2021, Sz. KozłowskiQuasar variability based on 1, 2, 3, and 4slides
9.4.2021, K. Kruszyńska"Bayesian Approach for Determining Microlens System Properties with High-angular-resolution Follow-up Imaging" Koshimoto, Bennett, and Suzuki 2020slides
26.3.2021, R. Poleski"Quantifying the Bayesian Evidence for a Planet in Radial Velocity Data" Nelson et al. 2020slides
12.3.2021, M. Gromadzki"Astrophysical Sources of Statistical Uncertainty in Precision Radial Velocities and Their Approximations" Beatty and Gaudi 2015slides
14.1.2021, M. Ratajczak"The Joker: A Custom Monte Carlo Sampler for Binary-star and Exoplanet Radial Velocity Data" Price-Whelan et al. 2017slides
7.1.2021, P. Zieliński"Detecting extrasolar planets from stellar radial velocities using Bayesian evidence" Feroz et al. 2011slides
10.12.2020, R. Poleski"Multimodal nested sampling: an efficient and robust alternative to Markov Chain Monte Carlo methods for astronomical data analyses" Feroz and Hobson 2008slides, code, data
26.11.2020, Ł. Wyrzykowski"Dos and don'ts of reduced chi-squared" Andrae et al. 2010slides
19.11.2020, J. SkowronIntroduction to MCMCslides, more slides, code 1, code 2, data
29.10.2020, R. PoleskiBayes' theorem and related conceptsslides

Statistical topics that can be discussed:

In random order: