Related papers: Bayesian correction of $H(z)$ data uncertainties
We show that the 32 $H(z)$ data from cosmic chronometers have overestimated uncertainties and make use of a Bayesian method to correct and reduce it. We then use the corrected data to constrain flat $\Lambda$CDM and O$\Lambda$CDM…
We compile a complete collection of reliable Hubble parameter $H(z)$ data to redshift $z \leq 2.36$ and use them with the Gaussian Process method to determine continuous $H(z)$ functions for various data subsets. From these continuous…
We analyze how predictions of cosmological models depend on a choice of described observational data, restrictions on flatness, and how this choice can alleviate the $H_0$ tension. These effects are demonstrated in the $w$CDM model in…
The $\Lambda$CDM model faces several tensions with recent cosmological data and their increased accuracy. The mismatch between the values of the Hubble constant $H_0$ obtained from direct distance ladder measurements and from the cosmic…
We use updated Hubble parameter and baryon acoustic oscillation data, as well as other lower-redshift Type Ia supernova, Mg II reverberation-measured quasar, quasar angular size, H II starburst galaxy, and Amati-correlated gamma-ray burst…
In this Comment we discuss a recent analysis by Yu et al. [RAA 11, 125 (2011)] about constraints on the smoothness $\alpha$ parameter and dark energy models using observational $H(z)$ data. It is argued here that their procedure is…
Aiming at exploring the nature of dark energy, we use thirty-six observational Hubble parameter data (OHD) in the redshift range $0 \leqslant z \leqslant 2.36$ to make a cosmological model-independent test of the two-point…
We perform the improved constraints on the Hubble constant $H_0$ by using the model-independent method, Gaussian Processes. Utilizing the latest 36 $H(z)$ measurements, we obtain $H_0=69.21\pm3.72$ km s$^{-1}$ Mpc$^{-1}$, which is…
In the realm of the $\omega$CDM cosmological model with quiescence or quintessence as the dark energy, characterized by $\omega>-1$, there exists a fixed value of $H(z)$ at $z=-1$, devoid of dependency on other cosmological parameters. To…
While Bayesian model selection is a useful tool to discriminate between competing cosmological models, it only gives a relative rather than an absolute measure of how good a model is. Bayesian doubt introduces an unknown benchmark model…
Two-point diagnostics $Om(z_i,z_j)$ and $Omh^2(z_i,z_j)$ have been introduced as an interesting tool for testing the validity of the $\Lambda$CDM model. Quite recently, Sahni, Shafieloo $\&$ Starobinsky (2014) combined two independent…
Adopting the low-redshift observational datasets, including the Pantheon sample of Type Ia supernovae, baryon acoustic oscillation measurements, and the tomographic Alcock-Paczynski method, we determine the Hubble constant to be…
We use three different data sets, specifically $H(z)$ measurements from cosmic chronometers, the HII-galaxy Hubble diagram, and reconstructed quasar-core angular-size measurements, to perform a joint analysis of three flat cosmological…
Quantifying uncertainty and updating reliability are essential for ensuring the safety and performance of engineering systems. This study develops a hierarchical Bayesian modeling (HBM) framework to quantify uncertainty and update…
In this paper, we use a set of observational $H(z)$ data (OHD) to constrain the $\Lambda$CDM cosmology. This data set can be derived from the differential ages of the passively evolving galaxies. Meanwhile, the $\mathcal {A}$-parameter,…
Recently, Sahni, Shafielo o & Starobinsky (2014) combined two independent measurements of $H(z)$ from BAO data with the value of the Hubble constant $H_0 = H(z=0)$, in order to test the cosmological constant hypothesis by means of an…
Observational constraints are considered on a $w_{log}$CDM model of the dark energy equation of state, $w_{d}(z) = w_{0} + w_{a}\left( \frac{\ln(2+z)}{1+z} - \ln 2 \right)$, using the most recent cosmological datasets including DESI Baryon…
The $\Lambda$CDM model provides a good fit to a large span of cosmological data but harbors areas of phenomenology. With the improvement of the number and the accuracy of observations, discrepancies among key cosmological parameters of the…
Estimates of the Hubble constant, $H_0$, from the distance ladder and the cosmic microwave background (CMB) differ at the $\sim$3-$\sigma$ level, indicating a potential issue with the standard $\Lambda$CDM cosmology. Interpreting this…
Bayesian (Probabilistic) Machine Learning is used to probe the opacity of the Universe. It relies on a generative process where the model is the key object to generate the data involving the unknown parameters of the model, our prior…