2,747 research outputs found
A k-generalized statistical mechanics approach to income analysis
This paper proposes a statistical mechanics approach to the analysis of
income distribution and inequality. A new distribution function, having its
roots in the framework of k-generalized statistics, is derived that is
particularly suitable to describe the whole spectrum of incomes, from the
low-middle income region up to the high-income Pareto power-law regime.
Analytical expressions for the shape, moments and some other basic statistical
properties are given. Furthermore, several well-known econometric tools for
measuring inequality, which all exist in a closed form, are considered. A
method for parameter estimation is also discussed. The model is shown to fit
remarkably well the data on personal income for the United States, and the
analysis of inequality performed in terms of its parameters reveals very
powerful.Comment: LaTeX2e; 15 pages with 1 figure; corrected typo
k-Generalized Statistics in Personal Income Distribution
Starting from the generalized exponential function
, with
, proposed in Ref. [G. Kaniadakis, Physica A \textbf{296},
405 (2001)], the survival function ,
where , , and , is
considered in order to analyze the data on personal income distribution for
Germany, Italy, and the United Kingdom. The above defined distribution is a
continuous one-parameter deformation of the stretched exponential function
\textemdash to which reduces as
approaches zero\textemdash behaving in very different way in the and
regions. Its bulk is very close to the stretched exponential one,
whereas its tail decays following the power-law
. This makes the
-generalized function particularly suitable to describe simultaneously
the income distribution among both the richest part and the vast majority of
the population, generally fitting different curves. An excellent agreement is
found between our theoretical model and the observational data on personal
income over their entire range.Comment: Latex2e v1.6; 14 pages with 12 figures; for inclusion in the APFA5
Proceeding
Status of Lattice QCD
Significant progress has recently been achieved in the lattice gauge theory
calculations required for extracting the fundamental parameters of the standard
model from experiment. Recent lattice determinations of such quantities as the
kaon parameter, the mass of the quark, and the strong coupling constant
have produced results and uncertainties as good or better than the best
conventional determinations. Many other calculations crucial to extracting the
fundamental parameters of the standard model from experimental data are
undergoing very active development. I review the status of such applications of
lattice QCD to standard model phenomenology, and discuss the prospects for the
near future.Comment: 20 pages, 8 embedded figures, uuencoded, 2 missing figures. (Talk
presented at the Lepton-Photon Symposium, Cornell University, Aug. 10-15,
1993.
Recommended from our members
Evolving graphs: dynamical models, inverse problems and propagation
Applications such as neuroscience, telecommunication, online social networking,
transport and retail trading give rise to connectivity patterns that change over time.
In this work, we address the resulting need for network models and computational
algorithms that deal with dynamic links. We introduce a new class of evolving
range-dependent random graphs that gives a tractable framework for modelling and
simulation. We develop a spectral algorithm for calibrating a set of edge ranges from
a sequence of network snapshots and give a proof of principle illustration on some
neuroscience data. We also show how the model can be used computationally and
analytically to investigate the scenario where an evolutionary process, such as an
epidemic, takes place on an evolving network. This allows us to study the cumulative
effect of two distinct types of dynamics
The k-generalized distribution: A new descriptive model for the size distribution of incomes
This paper proposes the k-generalized distribution as a model for describing
the distribution and dispersion of income within a population. Formulas for the
shape, moments and standard tools for inequality measurement - such as the
Lorenz curve and the Gini coefficient - are given. A method for parameter
estimation is also discussed. The model is shown to fit extremely well the data
on personal income distribution in Australia and the United States.Comment: 12 pages with 8 figures; LaTeX; introduction revised, added reference
for section 1; accepted for publication in Physica A: Statistical Mechanics
and its Application
Kinetic distance and kinetic maps from molecular dynamics simulation
Characterizing macromolecular kinetics from molecular dynamics (MD)
simulations requires a distance metric that can distinguish
slowly-interconverting states. Here we build upon diffusion map theory and
define a kinetic distance for irreducible Markov processes that quantifies how
slowly molecular conformations interconvert. The kinetic distance can be
computed given a model that approximates the eigenvalues and eigenvectors
(reaction coordinates) of the MD Markov operator. Here we employ the
time-lagged independent component analysis (TICA). The TICA components can be
scaled to provide a kinetic map in which the Euclidean distance corresponds to
the kinetic distance. As a result, the question of how many TICA dimensions
should be kept in a dimensionality reduction approach becomes obsolete, and one
parameter less needs to be specified in the kinetic model construction. We
demonstrate the approach using TICA and Markov state model (MSM) analyses for
illustrative models, protein conformation dynamics in bovine pancreatic trypsin
inhibitor and protein-inhibitor association in trypsin and benzamidine
Physical origin of the power-law tailed statistical distributions
Starting from the BBGKY hierarchy, describing the kinetics of nonlinear
particle system, we obtain the relevant entropy and stationary distribution
function. Subsequently, by employing the Lorentz transformations we propose the
relativistic generalization of the exponential and logarithmic functions. The
related particle distribution and entropy represents the relativistic extension
of the classical Maxwell-Boltzmann distribution and of the Boltzmann entropy
respectively and define the statistical mechanics presented in [Phys. Rev. E
{\bf 66}, 056125 (2002)] and [Phys. Rev. E {\bf 72}, 036108 (2005). The
achievements of the present effort, support the idea that the experimentally
observed power law tailed statistical distributions in plasma physics, are
enforced by the relativistic microscopic particle dynamics.Comment: 6 pages. arXiv admin note: substantial text overlap with
arXiv:1110.3944, arXiv:1012.390
Fluctuating Hydrodynamics in a Dilute Gas
Hydrodynamic fluctuations in a dilute gas subjected to a constant heat flux are studied by both a computer simulation and the Landau-Lifshitz formalism. The latter explicitly incorporates the boundary conditions of the finite system, thus permitting quantitative comparison with the former. Good agreement is demonstrated
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