THE DOTHAN PRICING MODEL REVISITED

We compute zero‐coupon bond prices in the Dothan model by solving the associated PDE using integral representations of heat kernels and Hartman–Watson distributions. We obtain several integral formulas for the price P(t, T) at time t > 0 of a bond with maturity T > 0 that complete those of the original paper of Dothan, which are shown not to always satisfy the boundary condition P(T, T) = 1 .     

The frequency and size of price changes: evidence from non-parametric estimations

The majority of price setting models predict a negative correlation between the frequency and size of price changes. Using a unique micro-level price data from Slovakia, we find that a negative correlation between frequency and size of price changes holds only for more rigid prices. On the other hand, less rigid prices such as gasoline prices exhibit positive correlation in line with Rotemberg's pricing model.     

Internet Based Benchmarking

We discuss the design of interactive, internet based benchmarking using parametric (statistical) as well as non-parametric (DEA) models. The user receives benchmarks and improvement potentials. The user is also given the possibility to search different efficiency frontiers and hereby to explore alternative improvement strategies. Implementations of both a parametric and a non-parametric model are presented.     

The Relationship Between Discrepancies Defined on a Domain and on its Subset

The discrepancy is an important optimality criterion for experimental designs. Sometimes for practical reasons one may choose a design on some finite subset of the original experimental domain. This article addresses the question of whether minimum discrepancy designs are the same for the discrepancy defined on the original experimental domain and the discrepancy defined on a subset. Under certain non-trivial conditions they are shown to be equivalent. Examples are given to show when these conditions apply.     

Some asymptotic results of a non‐parametric conditional mode estimator for functional time‐series data

We consider the estimation of the conditional mode function when the covariates take values in some abstract function space. The main goal of this paper was to establish the almost complete convergence and the asymptotic normality of the kernel estimator of the conditional mode when the process is assumed to be strongly mixing and under the concentration property over the functional regressors. Some applications are given. This approach can be applied in time‐series analysis to the prediction and confidence band building. We illustrate our methodology by using El Nio data.     

工业效率与中国增长极形成的关系研究——基于中国地级市数据的实证检验和理论解释

本文阐述了工业效率的提升对增长极形成的作用机理。在此基础上,选用了城市区域贡献率水平、城市区域增长率水平和城市区域发展水平三个判定条件,运用核密度估计法对2001—2018年中国200个地级市,是否成为中国经济增长极进行了筛选和识别。本文实证检验了工业效率提升对增长极形成的作用机制,发现工业效率的提升能够显著推动增长极形成,其作用的过程机理是工业效率的提升一方面直接推动增长极形成,另一方面通过产业结构的升级间接地推动增长极的形成。同时发现,道路基础设施和互联网基础设施是通过促进工业效率提升,间接影响增长极的形成。人口规模和地方财政科技支出对增长极的形成也有显著正向影响。     

基于Mel系数和SVM的语音识别技术研究

本文研究了一种运用Mel频标倒谱系数作为特征参数和多分类支持向量机进行语音识别的方法。根据已有的分类方法,尝试将一种基于二叉树的多分类支持向量机用于语音识别。实验表明,基于Mel倒谱和多分类支持向量机的语音识别方法使系统的性能和速度大大提高,具有理想的识别效果和应用价值。     

Frontier Production Functions and Technical Efficiency Measures

The concept of technical efficiency is central to measuring the firm performance. The measurement of technical efficiency has proved difficult and complex, and the literature provides a range of methodologies. This paper reviews the various methodologies for measuring technical efficiency and offers a comparison between established methods of measurements. The discussion is literary with less mathematical jargons and equations. The objective of this paper is not to be exhaustive, but to be up‐to‐date and to provide a significant discussion on some of the core methods of measuring technical efficiency.     

Remarks on the strong law of large numbers for a triangular array of associated random variables

A strong law of large numbers for a triangular array of strictly stationary associated random variables is proved. It is used to derive the pointwise strong consistency of kernel type density estimator of the one-dimensional marginal density function of a strictly stationary sequence of associated random variables, and to obtain an improved version of a result by Van Ryzin (1969) on the strong consistency of density estimator for a sequence of independent and identically distributed random variables.     

Nonparametric methods with applications to hedonic models

Current real estate statistical valuation involves the estimation of parameters within a posited specification. Suchparametric estimation requires judgment concerning model (1) variables; and (2) functional form. In contrast,nonparametric regression estimation requires attention to (1) but permits greatly reduced attention to (2). Parametric estimators functionally model the parameters and variables affectingE(y¦x) while nonparametric estimators directly modelpdf(y, x) and henceE(y¦x).This article applies the kernel nonparametric regression estimator to two different data sets and specifications. The article shows the nonparametric estimator outperforms the standard parametric estimator (OLS) across variable transformations and across data subsets differing in quality. In addition, the article reviews properties of nonparametric estimators, presents the history of nonparametric estimators in real estate, and discusses a representation of the kernel estimator as a nonparametric grid method.