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The gaussian spread regression model for the calibration of site specific ensemble temperature forecasts depends on the apparently restrictive assumption that the uncertainty around temperature forecasts is normally distributed. We…

Atmospheric and Oceanic Physics · Physics 2007-05-23 Stephen Jewson

When searching for exoplanets, one wants to count how many planets orbit a given star, and to determine what their characteristics are. If the estimated planet characteristics are too far from those of a planet truly present, this should be…

Instrumentation and Methods for Astrophysics · Physics 2025-03-25 Nathan C. Hara , Thibault de Poyferré , Jean-Baptiste Delisle , Marc Hoffmann

Despite compelling theoretical arguments, the use of clusters as cosmological probes is, in practice, frequently questioned because of the many uncertainties impinging on cluster mass estimates. Our aim is to develop a fully self-consistent…

Cosmology and Nongalactic Astrophysics · Physics 2017-11-29 M. Pierre , A. Valotti , L. Faccioli , N. Clerc , R. Gastaud , E. Koulouridis , F. Pacaud

Binary observations are often repeated to improve data quality, creating technical replicates. Several scoring methods are commonly used to infer the actual individual state and obtain a probability for each state. The common practice of…

Methodology · Statistics 2025-01-24 Manuela Royer-Carenzi , Hadrien Lorenzo , Pierre Pudlo

We implement the method developed in [1] to construct the most general parametrised action for linear cosmological perturbations of bimetric theories of gravity. Specifically, we consider perturbations around a homogeneous and isotropic…

General Relativity and Quantum Cosmology · Physics 2017-01-27 Macarena Lagos , Pedro G. Ferreira

We have used recent X-ray and optical data in order to impose some constraints on the cosmology and cluster scaling relations. Generically two kind of hypotheses define our model. First we consider that the cluster population is well…

Astrophysics · Physics 2009-10-31 J. M. Diego , E. Martinez-Gonzalez , J. L. Sanz , L. Cayon , J. Silk

The comparison of the Standard Cosmological Model (SCM) with astronomical observations, i.e. theory versus experiment, and with the Minimal Standard Model (MSM) in particle physics, i.e. theory versus theory, is discussed. The main issue of…

High Energy Physics - Phenomenology · Physics 2007-05-23 A. D. Dolgov

Cosmological observations are beginning to reach a level of precision that allow us to test some of the most fundamental assumptions in our working model of the Universe. One such an assumption is that gravity is governed by the General…

Cosmology and Nongalactic Astrophysics · Physics 2019-09-11 Pedro G. Ferreira

The anthropic principle is an inevitable constraint on the space of possible theories. As such it is central to determining the limits of physics. In particular, we contend that what is ultimately possible in physics is determined by…

General Relativity and Quantum Cosmology · Physics 2010-02-11 Navin Sivanandam

A new cosmological test is derived, based on the distribution of individual V/Vmax in a complete redshift-limited sample of distant objects. The fundamental assumption is that, in any bin of absolute luminosity, individual V/Vmax are…

Astrophysics · Physics 2007-05-23 L. Van Waerbeke , G. Mathez , Y. Mellier , H. Bonnet , M. Lachieze-Rey

We present a novel test of the cosmological principle: the idea that, on sufficiently large scales, the universe should appear homogeneous and isotropic to observers comoving with the Hubble flow. This is a fundamental assumption in modern…

Cosmology and Nongalactic Astrophysics · Physics 2023-05-19 Oliver T. Oayda , Geraint F. Lewis

Model selection in clustering requires (i) to specify a suitable clustering principle and (ii) to control the model order complexity by choosing an appropriate number of clusters depending on the noise level in the data. We advocate an…

Information Theory · Computer Science 2010-06-03 Joachim M. Buhmann

This paper studies the problem of distributed classification with a network of heterogeneous agents. The agents seek to jointly identify the underlying target class that best describes a sequence of observations. The problem is first…

Artificial Intelligence · Computer Science 2020-11-24 James Z. Hare , Cesar A. Uribe , Lance Kaplan , Ali Jadbabaie

We propose a multi-scale extension of conformal prediction, an approach that constructs prediction sets with finite-sample coverage guarantees under minimal statistical assumptions. Classic conformal prediction relies on a single notion of…

Statistics Theory · Mathematics 2025-02-11 Ali Baheri , Marzieh Amiri Shahbazi

We compare two approaches to embedding joint distributions of random variables recorded under different conditions (such as spins of entangled particles for different settings) into the framework of classical, Kolmogorovian probability…

Probability · Mathematics 2015-06-18 Ehtibar N. Dzhafarov , Janne V. Kujala

A theory of measurement uncertainty is presented, which, since it is based exclusively on the Bayesian approach and on the subjective concept of conditional probability, is applicable in the most general cases. The recent International…

Data Analysis, Statistics and Probability · Physics 2008-02-03 G. D'Agostini

Most computer vision application rely on algorithms finding local correspondences between different images. These algorithms detect and compare stable local invariant descriptors centered at scale-invariant keypoints. Because of the…

Computer Vision and Pattern Recognition · Computer Science 2014-09-10 Ives Rey-Otero , Mauricio Delbracio , Jean-Michel Morel

Cosmography, as an integral branch of cosmology, strives to characterize the Universe without relying on pre-determined cosmological models. This model-independent approach utilizes Taylor series expansions around the current epoch,…

General Physics · Physics 2024-06-11 Seokcheon Lee

Monte Carlo experiments produce samples in order to estimate features of a given distribution. However, simultaneous estimation of means and quantiles has received little attention, despite being common practice. In this setting we…

Computation · Statistics 2020-04-24 Nathan Robertson , James M. Flegal , Dootika Vats , Galin L. Jones

Practitioners making decisions based on causal effects typically ignore structural uncertainty. We analyze when this uncertainty is consequential enough to warrant methodological solutions (Bayesian model averaging over competing causal…

Machine Learning · Computer Science 2025-08-01 Maurits Kaptein