Related papers: The reliability of the AIC method in Cosmological …

Coasting cosmology offers an intriguing and straightforward framework for understanding the universe. In this work, we employ the Trans-Planckian Censorship Criterion (TCC) conjecture to test the viability of the coasting cosmology and…

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…

Soft sensors have been extensively used to monitor key variables using easy-to-measure variables and mathematical models. Partial differential equations (PDEs) are model candidates for soft sensors in industrial processes with…

Motivated by recent works on the role of the Holographic principle in cosmology, we relate a class of second order Ricci invariants to the IR cutoff characterizing the holographic Dark Energy density. The choice of second order invariants…

Transient recurring phenomena are ubiquitous in many scientific fields like neuroscience and meteorology. Time inhomogenous Vector Autoregressive Models (VAR) may be used to characterize peri-event system dynamics associated with such…

A new compilation of $120$ angular-size/redshift data for compact radio quasars from very-long-baseline interferometry (VLBI) surveys motivates us to revisit the interaction between dark energy and dark matter with these probes reaching…

With the increasing importance of safety requirements associated with the use of black box models, evaluation of selective answering capability of models has been critical. Area under the curve (AUC) is used as a metric for this purpose. We…

We consider a non-linear interaction between the dark matter and dark energy components of the universe. In particular, within the FLRW geometry, where dark matter is described by a dust fluid and dark energy by an ideal gas with a constant…

Model selection and order selection problems frequently arise in statistical practice. A popular approach to addressing these problems in the frequentist setting involves information criteria based on penalised maxima of log-likelihoods for…

In cosmology many dramatically different scenarios with the past (big bang versus bounce) and in the future (de Sitter versus big rip) singularities are compatible with the present day observations. This difficulty is called the degeneracy…

This paper studies the model selection problem in a large class of causal time series models, which includes both the ARMA or AR($\infty$) processes, as well as the GARCH or ARCH($\infty$), APARCH, ARMA-GARCH and many others processes. We…

One of the main results of the ATIC (Advanced Thin Ionization Calorimeter) experiment is a collection of energy spectra of abundant cosmic-ray nuclei: protons, He, C, O, Ne, Mg, Si, Fe measured in terms of energy per particle in the energy…

Many studies are devoted to the design of radiomic models for a prediction task. When no effective model is found, it is often difficult to know whether the radiomic features do not include information relevant to the task or because of…

This paper introduces Kernel-based Information Criterion (KIC) for model selection in regression analysis. The novel kernel-based complexity measure in KIC efficiently computes the interdependency between parameters of the model using a…

Typical Bayesian methods for models with latent variables (or random effects) involve directly sampling the latent variables along with the model parameters. In high-level software code for model definitions (using, e.g., BUGS, JAGS, Stan),…

Dark energy plays a crucial role in the evolution of cosmic expansion. In most studies, dark energy is considered a single dynamic component. In fact, multi-component dark energy models may theoretically explain the accelerated expansion of…

Estimating the number of principal components is one of the fundamental problems in many scientific fields such as signal processing (or the spiked covariance model). In this paper, we first demonstrate that, for fixed $p$, any penalty term…

Information criteria have had a profound impact on modern ecological science. They allow researchers to estimate which probabilistic approximating models are closest to the generating process. Unfortunately, information criterion comparison…

The uncertainty-penalized information criterion (UBIC) has been proposed as a new model-selection criterion for data-driven partial differential equation (PDE) discovery. In this paper, we show that using the UBIC is equivalent to employing…

For dynamical dark energy with the barotropic equation of state we determine the mean values of parameters and their confidence ranges together with other cosmological parameters on the basis of different combined datasets. The used…