Related papers: Testing a quintessence model with CMBR peaks locat…
In this paper, we study statistical inference of change-points (CPs) in multi-dimensional sequence. In CP detection from a multi-dimensional sequence, it is often desirable not only to detect the location, but also to identify the subset of…
By using a tracking quintessence model we obtain that the position of the first Doppler peak in the spectrum of CMB anisotropies only depends on the topology of the universe, $\Omega_k$, for any value of the ratio…
The quintessence field coupled to the cosmic neutrino background (CNB) has been widely discussed as an alternative mechanism to address the coincidence problem. As it is well known, it is possible to extend such models to obtain…
We present new results for consistency of maximum likelihood estimators with a focus on multivariate mixed models. Our theory builds on the idea of using subsets of the full data to establish consistency of estimators based on the full…
This paper explores some sufficient conditions for the enhanced solvability of strong vector equilibrium problems, which can be established via a variational approach. Enhanced solvability here means existence of solutions, which are strong…
We study the problem of detecting the presence of a single unknown spike in a rectangular data matrix, in a high-dimensional regime where the spike has fixed strength and the aspect ratio of the matrix converges to a finite limit. This…
A model is presented that is applicable to a wide range of peak-shaped voltammetric signals. It may be used, via curve-fitting, to resolve severely overlapped peaks, irrespective of the degree(s) of reversibility of the electrode processes.…
We study the Planck CMB temperature at different scales through its derivatives up to second order, which allows one to characterize the local shape and isotropy of the field. The problem of having an incomplete sky in the calculation and…
Based on two independent samples X_1,...,X_m and X_{m+1},...,X_n drawn from multivariate distributions with unknown Lebesgue densities p and q respectively, we propose an exact multiple test in order to identify simultaneously regions of…
Concept Bottleneck Models (CBMs) first map raw input(s) to a vector of human-defined concepts, before using this vector to predict a final classification. We might therefore expect CBMs capable of predicting concepts based on distinct…
Within a Bayesian retrospective framework, we present a way of examining the distribution of \cps through a novel set estimator. For a given level, $\alpha$, we aim at smallest sets that cover all \cps with a probability of at least…
Attention has been recently drawn towards models in which inflation and quintessence schemes are unified. In such `quintessential inflation' models, a unique scalar field is required to play both the role of the inflaton and of the…
Quantum tangent kernel methods provide an efficient approach to analyzing the performance of quantum machine learning models in the infinite-width limit, which is of crucial importance in designing appropriate circuit architectures for…
Determining the presence of a potential optical source in the interest region is important for an imaging system and can be achieved by using hypothesis testing. The previous studies assume that the potential source is completely…
We develop general criteria to construct unified frameworks for inflation and quintessence which employ a unique scalar field to drive both. By using such a minimal theoretical framework we avoid having to fine-tune couplings and…
The statistics of the curvature quanta generated during a stage of inflationary expansion is used to derive a count response model for the large-scale phonons determining, in the concordance lore, the warmer and the cooler spots of the…
A case-based reasoning (CBR) system solves a new problem by retrieving `cases' that are similar to the given problem. If such a system can achieve high accuracy, it is appealing owing to its simplicity, interpretability, and scalability. In…
Two semimetrics on probability distributions are proposed, given as the sum of differences of expectations of analytic functions evaluated at spatial or frequency locations (i.e, features). The features are chosen so as to maximize the…
The present work is a sequel of our previous work Phys.Rev.D { 93}, 084018 (2016) [arXiv:1601.08175 [gr-qc]] cite{hap} which depicted a simple version of an inflationary quintessential model whose inflationary stage was described by a Higgs…
The likelihood function is central to both frequentist and Bayesian formulations of parametric statistical inference, and large-sample approximations to the sampling distributions of estimators and test statistics, and to posterior…