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An all-sky sample of 1227 visual binaries based on Washington Double Star catalogue is constructed to infer the IMF, mass ratio, and projected distance distribution with a dedicated population synthesis model. Parallaxes from Gaia DR2 and…
Prior information often takes the form of parameter constraints. Bayesian methods include such information through prior distributions having constrained support. By using posterior sampling algorithms, one can quantify uncertainty without…
Mixture model-based frameworks are very popular for statistical inference in clustering. While convenient for producing probabilistic estimates of cluster assignments and uncertainty, they are prone to misspecification, which can lead to…
We investigate the geometry of the maximal a posteriori (MAP) partition in the Bayesian Mixture Model where the component and the base distributions are chosen from conjugate exponential families. We prove that in this case the clusters are…
We study the base distribution in chart-based generative models on Riemannian manifolds. Standard methods sample in Euclidean tangent space and then map the sample to the manifold with a chart. This is convenient, but it changes the meaning…
In Bayesian classification, it is important to establish a probabilistic model for each class for likelihood estimation. Most of the previous methods modeled the probability distribution in the whole sample space. However, real-world…
We advocate for a new statistical principle that combines the most desirable aspects of both parameter inference and density estimation. This leads us to the predictively oriented (PrO) posterior, which expresses uncertainty as a…
We develop here a semiparametric Gaussian mixture model (SGMM) for unsupervised learning with valuable spatial information taken into consideration. Specifically, we assume for each instance a random location. Then, conditional on this…
We present new measurements of the centers for 65 Milky Way globular clusters. Centers were determined by fitting ellipses to the density distribution within the inner $2\arcmin$ of the cluster center, and averaging the centers of these…
The task of parametric model selection is cast in terms of a statistical mechanics on the space of probability distributions. Using the techniques of low-temperature expansions, we arrive at a systematic series for the Bayesian posterior…
Extracting cosmological information from the Euclid galaxy survey will require modelling numerous systematic effects during the inference process. This implies varying a large number of nuisance parameters, which have to be marginalised…
The primary objects of study in information geometry are statistical manifolds, which are parametrized families of probability measures, induced with the Fisher-Rao metric and a pair of torsion-free conjugate connections. In recent work,…
Abridged: We have used the well-selected sample of ~1750 embedded, young, massive stars identified by the RMS survey to investigate the Galactic distribution of recent massive star formation. We describe the various methods used to assign…
We introduce a novel class of Bayesian mixtures for normal linear regression models which incorporates a further Gaussian random component for the distribution of the predictor variables. The proposed cluster-weighted model aims to…
We present detailed three-dimensional modelling of the stellar luminosity distribution for the disks of 31 relatively nearby (<= 110 Mpc) edge-on spiral galaxies. In contrast to most of the standard methods available in the literature we…
We estimate the variance $\xibar_2$, the skewness $\xibar_3$ and the kurtosis $\xibar_4$ in the distribution of density fluctuations in a complete sample from the APM Cluster Redshift Survey with 339 clusters and a mean depth $ \sim…
For two vast families of mixture distributions and a given prior, we provide unified representations of posterior and predictive distributions. Model applications presented include bivariate mixtures of Gamma distributions labelled as…
A model is developed for an idealised spherical galaxy evolving from a uniform mass distribution at the epoch of galactic separation until attaining an equilibrium state through gravitational collapse. The final theoretical radial surface…
Aims: Our scientific goal is to provide revised membership lists of the Alpha Per, Pleiades, and Praesepe clusters exploiting the second data release of Gaia and produce five-dimensional maps (ra, dec, parallax, pmRA, pmDEC) of these…
Over the last two decades, the Latent Position Model (LPM) has become a prominent tool to obtain model-based visualizations of networks. However, the geometric structure of the LPM is inherently symmetric, in the sense that outgoing and…