A Flexible Skew-Generalized Normal Distribution

Skew-symmetric distributions of various types have been the center of attraction by many researchers in the literature. In this article, we will introduce a uni/bimodal generalization of the Azzalini's skew-normal distribution which is indeed an extension of the skew-generalized normal distribution obtained by Arellano-Valle et al. (2004 Arellano-Valle , R. B. , Gómez , H. W. , Quintana , F. A. ( 2004 ). A new class of Skew-normal distributions . Commun. Statist. 33 : 1465 – 1480 .[Taylor & Francis Online] , [Google Scholar]). Our new distribution contains more parameters and thus it is more flexible in data modeling. Indeed, certain univariate case of the so called flexible skew-symmetric distribution of Ma and Genton (2004 Ma , Y. , Genton , M. G. ( 2004 ). Flexible class of skew-symmetric distributions . Scan. J. Statist. 31 : 459 – 468 .[Crossref], [Web of Science ®] , [Google Scholar]) is also a particular case of our proposed model. We will first study some basic distributional properties of the new extension, such as its distribution function, limiting behavior and moments. Then, we will investigate some useful results regarding its relation with other known distributions, such as student's t and skew-Cauchy distributions. In addition, we will present certain methods to generate the new distribution and, finally, we shall apply the model to a real data set to illustrate its behavior comparing to some rival models.     

Final outcome probabilities for SIR epidemic model

Abstract

We consider an SIR stochastic epidemic model in which new infections occur at rate f(x, y), where x and y are, respectively, the number of susceptibles and infectives at the time of infection and f is a positive sequence of real functions. A simple explicit formula for the final size distribution is obtained. Some efficient recursive methods are proved for the exact calculation of this distribution. In addition, we give a Gaussian approximation for the final distribution using a diffusion process approximation.     

Consistency of stochastic approximation algorithm with quasi-associated random errors

ABSTRACT

Many mathematical and physical problems are led to find a root of a real function f. This kind of equation is an inverse problem and it is difficult to solve it. Especially in engineering sciences, the analytical expression of the function f is unknown to the experimenter, but it can be measured at each point x_k with M(x_k) as expected value and induced error ξ_k. The aim is to approximate the unique root θ under some assumptions on the function f and errors ξ_k. We use a stochastic approximation algorithm that constructs a sequence (x_k)_{k ? 1}. We establish the almost complete convergence of the sequence (x_k)_k to the exact root θ by considering the errors (ξ_k)_k quasi-associated and we illustrate the method by numerical examples to show its efficiency.     

Dynamic Reliability Evaluation of Consecutive-k-Within-m-Out-of-n:F System

A consecutive k-within-m-out-of-n:F system consists of n linearly ordered components and fails if and only if there are m consecutive components which include among them at least k failed components. This system model generalizes both consecutive k-out-of-n:F and k-out-of-n:F systems. In this article, we study the dynamic reliability properties of consecutive k-within-m-out-of-n:F system consisting of exchangeable dependent components. We also obtain some stochastic ordering results and use them to get simple approximation formulae for the survival function and mean time to failure of this system.     

A Stochastic Simulation Approach to Model Selection for Stochastic Volatility Models

Stochastic volatility models have been widely appreciated in empirical finance such as option pricing, risk management, etc. Recent advances of Markov chain Monte Carlo (MCMC) techniques made it possible to fit all kinds of stochastic volatility models of increasing complexity within Bayesian framework. In this article, we propose a new Bayesian model selection procedure based on Bayes factor and a classical thermodynamic integration technique named path sampling to select an appropriate stochastic volatility model. The performance of the developed procedure is illustrated with an application to the daily pound/dollar exchange rates data set.     

Parameter Estimation for First-Order Random Coefficient Autoregressive (RCA) Models Based on Kalman Filter

In this article, we propose a new estimate algorithm for the parameters of a first-order Random Coefficient Autoregressive (RCA) Model. This algorithm turns out to be very reliable in estimating the true parameter values of a given model. It combines quasi-maximum likelihood method, the Kalman filter algorithm, and the Powell's method. Simulation results demonstrate that the algorithm is viable and promising.     

一个基于供求两方面的房价决定模型

运用经济计量方法设立模型,同时从供给与需求两方面考虑影响房价的因素,研究是供给决定了房价,还是需求决定了房价,并且区分其影响的大小.结论是房价与房屋造价和存款余额同方向变化,而与房屋的竣工面积反方向变化.控制房价的关键在于抑制宏观调控过热的经济所造成的房屋造价上升和加大住房建设面积.     

农户行为对我国农业技术进步类型影响的实证分析——以小麦为例

利用调查数据,运用logistic模型论证了农户行为受年龄、性别、自身素质和技术推广等因素影响,不同的农户行为对不同农业技术进步类型偏好不同,同时,农业技术推广人员对农户选择技术进步类型影响比较显著。最后,提出了我国要加大生物化学型农业技术的研发力度,要推行农民素质工程,大力提高农户科技知识水平;针对不同的农业技术、不同农户制定有针对性的农业技术推广方式等。     

我国企业社会责任会计信息需求分析

我国对企业社会责任会计及其信息披露的研究起步较晚,并且进展缓慢。这就需要我国会计学者根据我国对社会责任会计信息需求的实际情况,探索适合我国国情的社会责任会计信息披露方法。通过调查分析我国企业社会责任会计信息需求的现状,针对存在的问题提出建议和对策,以期促进我国企业与社会经济的和谐发展。     

网络环境下高校大学生信息需求调查分析——以河北工业大学图书馆读者为例

在现代信息环境中,读者信息需求正发生着深刻的变化。从河北工业大学读者信息需求调查结果分析,图书馆要充分满足用户的多样化、深层次信息需求,必须有针对性地通过丰富信息资源内容,提高图书馆信息服务能力,提升用户信息获取能力。