Advertisement

Topics

Maximum Entropy Principle in Statistical Inference: Case for Non-Shannonian Entropies.

08:00 EDT 29th March 2019 | BioPortfolio

Summary of "Maximum Entropy Principle in Statistical Inference: Case for Non-Shannonian Entropies."

In this Letter, we show that the Shore-Johnson axioms for the maximum entropy principle in statistical estimation theory account for a considerably wider class of entropic functional than previously thought. Apart from a formal side of the proof where a one-parameter class of admissible entropies is identified, we substantiate our point by analyzing the effect of weak correlations and by discussing two pertinent examples: two-qubit quantum system and transverse-momentum behavior of hadrons in high-energy proton-proton collisions.

Affiliation

Journal Details

This article was published in the following journal.

Name: Physical review letters
ISSN: 1079-7114
Pages: 120601

Links

DeepDyve research library

PubMed Articles [13087 Associated PubMed Articles listed on BioPortfolio]

Synthetic protein alignments by CCMgen quantify noise in residue-residue contact prediction.

Compensatory mutations between protein residues in physical contact can manifest themselves as statistical couplings between the corresponding columns in a multiple sequence alignment (MSA) of the pro...

Solvation Entropy Made Simple.

The entropies of molecules in solution are often calculated using gas phase formulae. It is assumed that, because implicit solvation models are fitted to reproduce free energies, this is sufficient fo...

Inferring interaction partners from protein sequences using mutual information.

Functional protein-protein interactions are crucial in most cellular processes. They enable multi-protein complexes to assemble and to remain stable, and they allow signal transduction in various path...

Entanglement Entropy and TTover ¯ Deformation.

Quantum gravity in a finite region of spacetime is conjectured to be dual to a conformal field theory (CFT) deformed by the irrelevant operator TT[over ¯]. We test this conjecture with entanglement e...

The maximum entropy production requirement for proton transfers enhances catalytic efficiency for β-lactamases.

Movement of charges during enzyme catalytic cycle may be due to conformational changes, or to fast electron or proton transfer, or to both events. In each case, entropy production can be calculated us...

Clinical Trials [4073 Associated Clinical Trials listed on BioPortfolio]

Intraoperative M-Entropy Measurements

The purpose of this study is to learn more about an Entropy monitor that your anesthesiologist will be using.

Validation of Phase Lag Entropy(PLE) as an Indicator of Depth of Sedation in Patients Undergoing Spinal Anesthesia

For verifying the phase lag entropy as the tool for measurement of level of consciousness, the investigators compared phase lag entropy to bispectral index. Using Target-Controlled Infusio...

BIS and Entropy in Deep Brain Simulation

The main objective of the study is to determine whether depth of anesthesia (DOA) monitoring such as Bispectral Index (BIS) and entropy are accurate in patients with neuro-psychological co...

Communication in Adolescents With ADHD

The interpersonal problems of adolescents with ADHD may be the most debilitating aspect of their psychopathologic behaviour. This being said, the investigators still do not have a clear un...

Comparison of the Bispectral Index and the Entropy of the Electroencephalogram During Total Intravenous Anesthesia

To compare Bispectral index and entropy during maintenance of anesthesia

Medical and Biotech [MESH] Definitions

The measure of that part of the heat or energy of a system which is not available to perform work. Entropy increases in all natural (spontaneous and irreversible) processes. (From Dorland, 28th ed)

Death resulting from the presence of a disease in an individual, as shown by a single case report or a limited number of patients. This should be differentiated from DEATH, the physiological cessation of life and from MORTALITY, an epidemiological or statistical concept.

Statistical formulations or analyses which, when applied to data and found to fit the data, are then used to verify the assumptions and parameters used in the analysis. Examples of statistical models are the linear model, binomial model, polynomial model, two-parameter model, etc.

Application of statistical procedures to analyze specific observed or assumed facts from a particular study.

Functions constructed from a statistical model and a set of observed data which give the probability of that data for various values of the unknown model parameters. Those parameter values that maximize the probability are the maximum likelihood estimates of the parameters.

Advertisement
Quick Search
Advertisement
Advertisement

 


DeepDyve research library

Searches Linking to this Article