试析集体名词的类及数

英语普通名词中的集体名词分为团体性集体名词、种类集体名词、个体性集体名词和概括性集体名词四类，它们的单复数型式各有不同。     

INFLUENCE DIAGNOSTICS IN PROPER DISPERSION MODELS

This paper discusses the application of influence diagnostic methods in univariate proper dispersion models. This class includes, in particular, continuous generalized linear models as well as other subclasses of continuous regression models. We emphasize the study of the local influence on the likelihood displacement and predictions from the models. Some of the diagnostics are illustrated by an example on directional data.     

可对称化矩阵特征值的Weyl型和Wielandt型扰动界

该文利用矩阵的奇异值分解得到了可对称化矩阵特征值的Weyl型和Wielandt型绝对扰动上界,并推广了Weyl-ЛиДский定理和Wielandt-Hoffman定理.     

（3＋1）维Kadomtsev-Petviashvili方程的N孤子解

利用Hirota双线性导数和形式摄动方法得到了（3＋1）维Kadomtsev-Petviashvili方程的单孤子解、双孤子解及N孤子解的解析表达式.     

曲面工件超声检测机器人误差补偿分析

针对曲面工件超声波检测过程中,超声检测机器人末端探头位姿误差对检测精度影响的问题。根据超声检测机器人自身特点,提出基于多关节摄动误差补偿原理逆向求解标定误差模型参数的方法,利用误差模型参数实现对检测中所有扫描点位姿误差的实时补偿,提高检测的精度。首先,应用Denavit-Hartenberg方法建立超声检测机器人的运动学模型;其次,分析超声检测机器人的误差原因和来源,并利用矩阵微分原理建立误差模型;最后,结合超声检测机器人测距功能和多关节摄动误差补偿原理得到位姿误差实时补偿方法。通过螺旋桨曲面工件扫描检测实验验证该位姿误差补偿方法的有效性。     

七对角线性方程组的追赶法

通过矩阵的分解,利用求解三对角线性方程组的有效方法——追赶法．探究其求解七对角线性方程组的算法,并对其算法在计算速度、占用内存方面进行估计．并用数值试验印证了相关结论．     

基于非仿射随机波动率模型的期权定价研究

本文应用快速傅里叶变换(FFT)方法, 考虑了标的资产服从非仿射随机波动率模型下的期权定价问题。首先, 应用偏微分方程扰动分析法, 得到了标的资产对数价格分布的近似特征函数; 然后, 应用傅里叶变换及其逆变换, 推导了欧式期权的拟闭型定价公式, 对此公式应用FFT方法可以快速得到高精度数值解。数值实验表明, FFT期权定价方法是非常精确的和有效的; 最后, 给出了基于恒生指数认购权证的实证研究。实证结果表明, 非仿射随机波动率期权定价模型比经典的Black-Scholes模型具有更高的定价精确性。     

Forecasting before,during, and after recession with singular spectrum analysis

The aim of this research is to apply the singular spectrum analysis (SSA) technique, which is a relatively new and powerful technique in time series analysis and forecasting, to forecast the 2008 UK recession, using eight economic time series. These time series were selected as they represent the most important economic indicators in the UK. The ability to understand the underlying structure of these series and to quickly identify turning points such as the on-set of the recent recession is of key interest to users. In recent years, the SSA technique has been further developed and applied to many practical problems. Hence, these series will provide an ideal practical test of the potential benefits from SSA during one of the most challenging periods for econometric analyses of recent years. The results are compared with those obtained using the ARIMA and Holt–Winters models as these methods are currently used as standard forecasting methods in the Office for National Statistics in the UK.