Related papers: Slicing cluster mass functions with a Bayesian raz…
We subject to an N-body numerical investigation our analysis of Paper I on the survival of stellar clusters undergoing rapid mass loss. We compare analytical tracks of bound mass-fraction {\it vs} star formation efficiency $\epsilon$ to…
In this chapter we review some examples, methods, and recent results involving comparison of clustering properties of point processes. Our approach is founded on some basic observations allowing us to consider void probabilities and moment…
We show how to obtain a Bayesian estimate of the rates or numbers of signal and background events from a set of events when the shapes of the signal and background distributions are known, can be estimated, or approximated; our method works…
This short document illustrates QLUSTER: a toy model for populations of binary black holes in dense astrophysical environments. QLUSTER is a simple tool to investigate the occurrence and properties of hierarchical black-hole mergers…
The task of clustering a set of objects based on multiple sources of data arises in several modern applications. We propose an integrative statistical model that permits a separate clustering of the objects for each data source. These…
We evaluate in a homogeneous way the optical masses of 170 nearby clusters (z< 0.15). The sample includes both data from the literature and the new ENACS data (Katgert et al. 1996, 1998). On the assumption that mass follows the galaxy…
Studies of the Galactic population of radio pulsars have shown that their luminosity distribution appears to be log-normal in form. We investigate some of the consequences that occur when one applies this functional form to populations of…
In this paper, we describe a procedure for modelling strong lensing galaxy clusters with parametric methods, and to rank models quantitatively using the Bayesian evidence. We use a publicly available Markov chain Monte-Carlo (MCMC) sampler…
We present a new method to model the mass distribution of galaxy clusters that combines a parametric and a free-form approach to reconstruct cluster cores with strong lensing constraints. It aims at combining the advantages of both…
We calculate the optical depth and the number of events due to gravitational microlensing towards the Galactic bulge, the spiral arm directions $\gamma$ Scutum, $\beta$ Scutum, $\gamma$ Normae, $\vartheta$ Muscae and some dwarf galaxies in…
Besides their intrinsic nuclear-structure value, nuclear mass models are essential for astrophysical applications, such as r-process nucleosynthesis and neutron-star structure. To overcome the intrinsic limitations of existing…
In order to cluster or partition data, we often use Expectation-and-Maximization (EM) or Variational approximation with a Gaussian Mixture Model (GMM), which is a parametric probability density function represented as a weighted sum of…
Fuzzy c-means clustering is widely used to identify cluster structures in high-dimensional data sets, such as those obtained in DNA microarray and quantitative proteomics experiments. One of its main limitations is the lack of a…
Clustering of proteins is of interest in cancer cell biology. This article proposes a hierarchical Bayesian model for protein (variable) clustering hinging on correlation structure. Starting from a multivariate normal likelihood, we enforce…
Context. Biases in mass measurements of galaxy clusters are one of the major limiting systematics in constraining cosmology with clusters. Aims. We aim to demonstrate that the systematics associated with cluster gravitational potentials are…
Bayesian model selection is a tool to decide whether the introduction of a new parameter is warranted by data. I argue that the usual sampling statistic significance tests for a null hypothesis can be misleading, since they do not take into…
The luminosity distribution of Galactic radio pulsars is believed to be log-normal in form. Applying this functional form to populations of pulsars in globular clusters, we employ Bayesian methods to explore constraints on the mean and…
We show that model-based Bayesian clustering, the probabilistically most systematic approach to the partitioning of data, can be mapped into a statistical physics problem for a gas of particles, and as a result becomes amenable to a…
A new method is presented for modelling the physical properties of galaxy clusters. Our technique moves away from the traditional approach of assuming specific parameterised functional forms for the variation of physical quantities within…
Motivated by previous findings that the magnitude gap between certain satellite galaxy and the central galaxy can be used to improve the estimation of halo mass, we carry out a systematic study of the information content of different member…