Related papers: Bayesian `Hyper-Parameters' Approach to Joint Esti…
We generalise the procedure for joint estimation of cosmological parameters to allow freedom in the relative weights of various probes. This is done by including in the joint Likelihood function a set of 'Hyper-Parameters', which are dealt…
We use a generalised procedure for the combined likelihood analysis of different cosmological probes, the `Hyper-Parameters' method, that allows freedom in the relative weights of the raw measurements. We perform a joint analysis of the…
We describe the Bayesian-based signal-to-noise eigenmode method for cosmological parameter estimation, show how it can be used to optimally compress large CMB anisotropy data sets to manageable sizes, and apply it to the DMR 4-year, South…
A method is presented for performing joint analyses of cosmological datasets, in which the weight assigned to each dataset is determined directly by it own statistical properties. The weights are considered in a Bayesian context as a set of…
To understand their data better, astronomers need to use statistical tools that are more advanced than traditional ``freshman lab'' statistics. As an illustration, the problem of combining apparently incompatible measurements of a quantity…
In this paper, we study the cosmological constraints from the measurements of Hubble parameters---$H(z)$ data. Here, we consider two kinds of $H(z)$ data: the direct $H_0$ probe from the Hubble Space Telescope (HST) observations of Cepheid…
Local measurements of the Hubble constant ($H_0$) based on Cepheids e Type Ia supernova differ by $\approx 5 \sigma$ from the estimated value of $H_0$ from Planck CMB observations under $\Lambda$CDM assumptions. In order to better…
Direct measurements of Hubble parameters $H(z)$ are very useful for cosmological model parameters inference. Based on them, Sahni, Shafieloo and Starobinski introduced a two-point diagnostic $Omh^2(z_i, z_j)$ as an interesting tool for…
We use Cosmic Microwave Background (CMB) observations together with the Red-sequence Cluster Survey (RCS) weak lensing results to derive constraints on a range of cosmological parameters. This particular choice of observations is motivated…
We present a unified Bayesian framework to jointly constrain the Hubble constant $H_0$ and the post-Newtonian parameter $\gamma$, a key probe of deviations from general relativity, using the population characteristics of strongly lensed…
We propose a Bayesian meta-analysis to infer the current expansion rate of the Universe, called the Hubble constant ($H_0$), via time delay cosmography. Inputs of the meta-analysis are estimates of two properties for each pair of…
We use simulated Hubble parameter data in the redshift range 0 \leq z \leq 2 to explore the role and power of observational H(z) data in constraining cosmological parameters of the {\Lambda}CDM model. The error model of the simulated data…
An intriguing discrepancy emerging in the concordance model of cosmology is the tension between the locally measured value of the Hubble rate, and the 'global' value inferred from the cosmic microwave background (CMB). This could be due to…
We propose an efficient Bayesian MCMC algorithm for estimating cosmological parameters from CMB data without use of likelihood approximations. It builds on a previously developed Gibbs sampling framework that allows for exploration of the…
We use 28 Hubble parameter, $H(z)$, measurements at intermediate redshifts $0.07 \leq z \leq 2.3$ to determine the present-day Hubble constant $H_0$ in four cosmological models. We measure $H_0 = 68.3^{ +2.7}_{ -2.6 }, 68.4^{ +2.9 }_{ -3.3…
Different measurements of the Hubble constant ($H_{0}$) are not consistent and a tension between the CMB based methods and cosmic distance ladder based methods has been observed. Measurements from various distance based methods are also…
The Hubble constant ${H}_0$ is a crucial parameter in cosmology. However, different cosmic observations have resulted in varying posterior results for ${H}_0$, leading to what is known as the ${H}_0$ tension. In order to address this issue,…
The Megamaser Cosmology Project inferred a value for the Hubble constant given by $H_0=73.9 \pm 3.0 $ km/sec/Mpc. This value was obtained using Bayesian inference by marginalizing over six nuisance parameters, corresponding to the…
We discuss the problems of applying Maximum Likelihood methods to the CMB and how one can make it both efficient and optimal. The solution is a generalised eigenvalue problem that allows virtually no loss of information about the parameter…
In this work, we reconstruct the H(z) based on observational Hubble data with Artificial Neural Network, then estimate the cosmological parameters and the Hubble constant. The training data we used are covariance matrix and mock H(z), which…