The Inequality Process Versus the Saved Wealth Model: Which Is the More Likely to Imply an Analogue of Thermodynamics in Social Science?

The Inequality Process (IP) and the Saved Wealth Model (SW) are theories of income distribution. The IP's social science metatheory requires its stationary distribution to fit the distribution of labor income conditioned on education. The SW is a modification of the particle system model of the kinetic theory of gases (KTG), the basis of gas thermodynamics. The IP is a particle system similar to the SW and KTG. This article shows that the IP passes the empirical test required of it by social science theory better than the SW. The IP's advantage increases as the U.S. labor force becomes more educated. The IP may the better bet to imply an analogue of thermodynamics in social science.     

Nonlinear continuous-discrete filtering using kernel density estimatesand functional integrals

We develop filter algorithms for nonlinear stochastic differential equations with discrete time measurements (continuous-discrete state space model). The apriori density (time update) is computed by Monte Carlo simulations of the Fokker-Planck equation using kernel density estimators and measurement updates are obtained by using the extended Kalman filter (EKF) updates. For small sampling intervals, a discretized continuous sampling approach (DCS) is used. A third algorithm utilizes a functional (path) integral representation of the transition density (functional integral filter FIF). The kernel density filter (KDF), DCS, and FIF are compared with the EKF and the Gaussian sum filter by using a Ginzburg-Landau-equation and a stochastic volatility model.     

A GENERATIVE MODEL OF INCOME DISTRIBUTION: FORMALIZATION WITH ITERATED INVESTMENT GAME

The purpose of this paper is to formalize a simple model that theoretically connects individuals' rational choice at the micro level to income distribution, which is subject to the Gibrat's law empirically, as social structure at macro level. We use an iterated investment game as a baseline model in which a player has a binary choice between investing and not investing. Given parameters which prescribe the payoff structure of the game are the prize density γ and the rate of return R. Method of analysis is a simulation with computation. We investigate changes in the Gini coefficient and skewness of the total profit distribution, as the parameters varied as follows: 0 ≤ γ ≤ 1, R = 0.5, 1, 2, 3, and n (the number of times that the game is repeated) = 5, 10. As a result of analysis, we derive the implication that the Gini coefficient increases up to critical point, where 0 ≤ γ ≤ 1/(R + 1), then decreases as prize density increases, where 1/(R + 1) < γ ≤ 1. Furthermore, we show that our model, with cumulative effect, generates a lognormal distribution under the condition that 1/(R + 1) < γ ≤ 1.     

Bayesian Inference and Prediction of Gaussian Random Fields Based on Censored Data

This work develops a Bayesian approach to perform inference and prediction in Gaussian random fields based on spatial censored data. These type of data occur often in the earth sciences due either to limitations of the measuring device or particular features of the sampling process used to collect the data. Inference and prediction on the underlying Gaussian random field is performed, through data augmentation, by using Markov chain Monte Carlo methods. Previous approaches to deal with spatial censored data are reviewed, and their limitations pointed out. The proposed Bayesian approach is applied to a spatial dataset of depths of a geologic horizon that contains both left- and right-censored data, and comparisons are made between inferences based on the censored data and inferences based on “complete data” obtained by two imputation methods. It is seen that the differences in inference between the two approaches can be substantial.     

Some inequalities and asymptotic formulas for eigenvalues on Riemannian manifolds

In this paper, we establish sharp inequalities for four kinds of classical eigenvalues in bounded domains of Riemannian manifolds. We also obtain the Weyl-type asymptotic formulas for the eigenvalues of the buckling and clamped plate problems in bounded domains of Riemannian manifolds. In addition, we give a negative answer to the Payne conjecture for the one-dimensional case.     

Some properties of a generalized Hamy symmetric function and its applications

This paper is concerned with the generalized Hamy symmetric function

     

Expansion formulas for the inertias of Hermitian matrix polynomials and matrix pencils of orthogonal projectors

This paper gives a group of expansion formulas for the inertias of Hermitian matrix polynomials A−A², I−A² and A−A³ through some congruence transformations for block matrices, where A is a Hermitian matrix. Then, the paper derives various expansion formulas for the ranks and inertias of some matrix pencils generated from two or three orthogonal projectors and Hermitian unitary matrices. As applications, the paper establishes necessary and sufficient conditions for many matrix equalities to hold, as well as many inequalities in the Löwner partial ordering to hold.     

一个求解非线性不等式约束优化问题的带有共轭梯度参数的广义梯度投影算法

本文提出一个求解非线性不等式约束优化问题的带有共轭梯度参数的广义梯度投影算法.算法中的共轭梯度参数是很容易得到的,且算法的初始点可以任意选取.而且,由于算法仅使用前一步搜索方向的信息,因而减少了计算量.在较弱条件下得到了算法的全局收敛性.数值结果表明算法是有效的.     

On dynamical behavior for optical solitons sustained by the perturbed Chen–Lee–Liu model

This study investigates the perturbed Chen–Lee–Liu model that represents the propagation of an optical pulse in plasma and optical fiber. The generalized exponential rational function method is used for this purpose. As a result, we obtain some non-trivial solutions such as the optical singular, periodic, hyperbolic, exponential, trigonometric soliton solutions. We aim to express the pulse propagation of the generated solutions, by taking specific values for the free parameters existed in the obtained solutions. The obtained results show that the generalized exponential rational function technique is applicable, simple and effective to get the solutions of nonlinear engineering and physical problems. Moreover, the acquired solutions display rich dynamical evolutions that are important in practical applications.