Meetings - every other week:

Organizer: Radek Poleski (email: rpoleski@...)

Date and speaker | Paper/Topic |
---|---|

???, ??? | ??? |

Paper | Title/topic | Notes |
---|---|---|

Dittmann 2024 | NEW - "Notes on the Practical Application of Nested Sampling: MultiNest, (Non)convergence, and Rectification" | |

Cappellari and Copin 2003 | NEW - " Adaptive spatial binning of integral-field spectroscopic data using Voronoi tessellations" | lots of citations |

Martínez-Gómez et al. 2014 | "Distance Correlation Methods for Discovering Associations in Large Astrophysical Databases" | somehow similar method to PCA |

Leistedt et al. 2023 | "Hierarchical Bayesian inference of photometric redshifts with stellar population synthesis models" | |

Perren, Vázquez and Piatti 2015 | "ASteCA: Automated Stellar Cluster Analysis" | densities of clusters analyzed |

Weigel, Schawinski and Bruderer 2016 | "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. 2020 | "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 2023 | "Modelling stellar activity with Gaussian process regression networks" | Gaussian processes and other methods |

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 |

Importance sampling | The 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 project | Student can present what statistical analysis they work on, even if it's not finished. It's likely that other participants will give useful suggestions | |

Schwarzenberg-Czerny 1996 | "An astronomer's guide to period searching" | short |

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 |

- likelihood analysis with non-gaussian noise
- mixture models
- coarse-grained leave-one-out likelihood
- accuracy of period determination
- expectation maximization algorithm
- Q-Q plots and Worm plots
- robust fitting
- graphical Bayesian network
- Bayesian blocks
- Gibbs sampling
- non-negative matrix factorization
- mixture density network
- bayesian alternative for K-S test
- sequential nested sampling
- beta mixture model
- effective complexity of models
- bimodality detection
- dynamic temperature selection for parallel tempering in MCMC
- nonnegative matrix factorization
- variational Bayesian methods
- phase distance correlation periodogram
- distance correlation coefficient
- hierarchical Bayesian inference
- Bayesian model selection
- generalised Lomb-Scargle periodogram
- Lucy and Sweeney bias
- gaussian mixture models
- Ve/Va method
- cross-validation
- principial component analysis
- Bayesian model validation
- guassian process
- approximate Bayesian computation
- nested sampling
- hierarchical clustering forest
- posterior inverse percentile distribution
- ensemble slice sampling
- Thompson multitaper
- model selection
- statistical evidence
- non-parametric iterative smoothing
- Lomb-Scargle periododgram