Estimating the fundamental frequency of a periodic function

In this paper we consider the problem of estimation of the fundamental frequency of a periodic function, which has several applications in Speech Signal Processing. The problem was originally proposed by Hannan (1974) and later on Quinn and Thomson (1991) provided an estimation procedure of the unknown parameters. It is observed that the estimation procedure of Quinn and Thomson (1991) is quite involved numerically. In this paper we propose to use two simple estimators and it is observed that their performance are quite satisfactory. Asymptotic properties of the proposed estimators are obtained. The large sample properties of the estimators are compared theoretically. We present some simulation results to compare their small sample performance. One speech data is analyzed using this particular model.     

A general algorithm to fit constrained DEDICOM models

The DEDICOM model is a model to analyze square tables describing asymmetric relationships among n entities. Its importance in the asymmetric multidimensional scaling literature is due to the fact that several authors showed a large class of models to be simply a constrained version of DEDICOM. A typical example is the Generalized GIPSCAL proposed by Kiers & Takane. In this paper we present a new algorithm capable to fit, in the least squares sense, any DEDICOM constrained model.     

中小企业融资与信用担保制度

资金不足目前已成为我国中小企业发展中最为突出的问题,融资困难成为制约中小企业发展的“瓶颈”,而担保困难又是“瓶颈”中的“瓶颈”,使得银行及其它金融机构为规避自身风险不愿对中小企业融资,从而造成中小企业的发展得不到足够的资金支持。我国目前的信用担保业尚未形成体系,其机构设置、运行机制、业务范围、风险控制、配套机制等方面均存在缺陷。借鉴国外的成功经验,构建一个具有中国特色的信用担保体系迫在眉睫。     

商业银行的中小企业信贷风险因素及其管理对策

中小企业信贷风险高被认为是造成其融资难的关键原因,也是商业银行信贷风险管理的难点之一.实证调查的结果表明,影响中小企业信贷风险的因素可归纳为企业、银行和环境三大方面十二个关键因素.就商业银行可控因素而言,应从内控机制等四方面入手化解中小企业信贷风险.但不同的被试类别对风险因素和策略表现出不同的看法.     

Estimation of a Change Point in a Hazard Function Based on Censored Data

The hazard function plays an important role in reliability or survival studies since it describes the instantaneous risk of failure of items at a time point, given that they have not failed before. In some real life applications, abrupt changes in the hazard function are observed due to overhauls, major operations or specific maintenance activities. In such situations it is of interest to detect the location where such a change occurs and estimate the size of the change. In this paper we consider the problem of estimating a single change point in a piecewise constant hazard function when the observed variables are subject to random censoring. We suggest an estimation procedure that is based on certain structural properties and on least squares ideas. A simulation study is carried out to compare the performance of this estimator with two estimators available in the literature: an estimator based on a functional of the Nelson-Aalen estimator and a maximum likelihood estimator. The proposed least squares estimator tums out to be less biased than the other two estimators, but has a larger variance. We illustrate the estimation method on some real data sets.     

On shrinkage least squares estimation in a parallelism problem

In a multi-sample simple regression model, generally, homogeneity of the regression slopes leads to improved estimation of the intercepts. Analogous to the preliminary test estimators, (smooth) shrinkage least squares estimators of Intercepts based on the James-Stein rule on regression slopes are considered. Relative pictures on the (asymptotic) risk of the classical, preliminary test and the shrinkage least squares estimators are also presented. None of the preliminary test and shrinkage least squares estimators may dominate over the other, though each of them fares well relative to the other estimators.     

Superiority comparisons between mixed regression estimators

This paper gives necessary and sufficient conditions for a mixed regression estimator to be superior to another mixed estimator. The comparisons are based on the mean square error matrices of the estimators. Both estimators are allowed to be biased.     

Multiple Linear Regression Model Under Nonnormality

Abstract

We consider multiple linear regression models under nonnormality. We derive modified maximum likelihood estimators (MMLEs) of the parameters and show that they are efficient and robust. We show that the least squares esimators are considerably less efficient. We compare the efficiencies of the MMLEs and the M estimators for symmetric distributions and show that, for plausible alternatives to an assumed distribution, the former are more efficient. We provide real-life examples.     

质疑“皇权不下县”——基于宏观的长时段的动态历史考证

自秦汉至明清之际的1 800余年，中国历代王朝的“编户齐民”一直在2 000万人至6 000万人之间徘徊，全国的耕地面积基本维持在8亿亩左右，县的数量大体保持在1 500个上下，总体上并没有达到“地方百里、人口万户”的标准建制，因而属于一种“小县制”。同时，县以下还有乡里制度和以什伍编制为基本组织原则的保甲体系，皇权专制集权统治以“县政”为依托，其政治影响可谓无所不在、无事不管。因此，由当代西方学者提出的所谓“国权不下县，县下惟宗族，宗族皆自治，自治靠伦理，伦理造乡绅”纯属于一种毫无历史根据和主观臆断的无稽之谈。     

中小企业信贷配给综合模型分析

为了考察中小企业比大企业更经常受到银行信贷配给约束的原因,在综合考虑银行利率、银行贷款审查成本、抵押品价值、企业风险、企业产权特征、企业规模、企业与银行之间的信息不对称程度、企业履约概率等多个因素的基础上,建立了中小企业信贷市场信贷配给综合模型。研究结果表明:中小企业规模小、私有产权比重大、难以提供有效的抵押品,以及中小企业与银行之间存在的信息不对称现象,是导致我国中小企业信贷市场融资困境的主要原因。此外,当综合考虑多个影响因素时,中小企业信贷市场的特征将会呈现更加复杂的结果。