Semiparametric Regression Smoothing of Non-linear Time Series

In this paper, we consider using a semiparametric regression approach to modelling non-linear autoregressive time series. Based on a finite series approximation to non-parametric components, an adaptive selection procedure for the number of summands in the series approximation is proposed. Meanwhile, a large sample study is detailed and a small sample simulation for the Mackey–Glass system is presented to support the large sample study.     

NONPARAMETRIC AUTOCOVARIANCE FUNCTION ESTIMATION

Nonparametric estimators of autocovariance functions for non-stationary time series are developed. The estimators are based on straightforward nonparametric mean function estimation ideas and allow use of any linear smoother (e.g. smoothing spline, local polynomial). The paper studies the properties of the estimators, and illustrates their usefulness through application to some meteorological and seismic time series.     

Graphical Techniques for Selecting Explanatory Variables for Time Series Data

Bayesian model building techniques are developed for data with a strong time series structure and possibly exogenous explanatory variables that have strong explanatory and predictive power. The emphasis is on finding whether there are any explanatory variables that might be used for modelling if the data have a strong time series structure that should also be included. We use a time series model that is linear in past observations and that can capture both stochastic and deterministic trend, seasonality and serial correlation. We propose the plotting of absolute predictive error against predictive standard deviation. A series of such plots is utilized to determine which of several nested and non-nested models is optimal in terms of minimizing the dispersion of the predictive distribution and restricting predictive outliers. We apply the techniques to modelling monthly counts of fatal road crashes in Australia where economic, consumption and weather variables are available and we find that three such variables should be included in addition to the time series filter. The approach leads to graphical techniques to determine strengths of relationships between the dependent variable and covariates and to detect model inadequacy as well as determining useful numerical summaries.     

《阿Q正传》艺术谱系析解

《阿Q正传》的艺术谱系可从叙事与形象两方面采用作品细读的方法来查考。《阿Q正传》的叙事手法与中国小说的史传式叙事手法恰相反对，而与《红楼梦》紧密相承；阿Q的精神气质是《庄子》“圣人”形象经历史积淀后的粗卑化呈现。     

用PLC构成产品分拣自控系统教学模型

可编程逻辑控制器简称为PLC ,它是以单片机为核心的工业控制专用机。最大特点是采用易学易懂的梯形图编制程序 ,梯形图符号和定义与继电器展开图完全一致。用PLC设计自控应用系统无需掌握复杂的计算机硬件原理就可编程实现 ,且PLC性能稳定可靠 ,使用灵活方便。本文通过产品分拣自控系统教学模型的原理分析 ,介绍了如何利用PLC中的高速计数器实现位移和速度的控制。并对整个系统程序作了详细介绍     

我国房地产价格发展趋势研究

 本文从房地产价格的相关理论出发，主要从房地产需求、房地产供给、房地产金融和房地产宏观调控等角度对影响房价的因素进行了分析，并从实证角度分析了各因素对房价的影响。本研究运用近10年房地产价格季度数据和时间序列模型对房地产价格发展趋势进行预测，最后提出房地产价格发展预警和稳定房价的建议。     

基于分形理论的时尚商品价格预测问题研究

在研究时尚商品价格规律及影响因素的复杂性、不确定性的基础之上，提出了基于分形理论的时尚商品价格预测新方法。该方法首先运用重标极差法分析了时尚商品价格时间序列预测的可行性，然后根据分形统计模型，得到时尚商品历史价格时间序列的分形维数，通过不断增加新销售或预测得到新的记录方法，求得增加新记录后的新分形维数，由此可以预测出下一时间单位的商品销售价格。通过实例进行了方法检验和结果比较，取得了较为理想的预测结果，证明了该方法的可行性和有效性。     

半平面上有限级随机Dirichlet级数的增长性

证明了右半平面上有限级随机Dirichlet级数的增长性几乎必然与其在每条水平直线上的增长性相同。     

网络语言的兴起成因分析及其网络语言规范化问题

随着“网络时代”的来临,互联网络在中国的飞速发展和日益普及,网络交际这种全新的高科技交际模式已被越来越多的人所接受,网络语言极大地影响着21世纪信息社会。     

上市公司财务杠杆与绩效的相关性研究

通过对我国上市公司财务杠杆指标的实证分析,研究了公司财务杠杆与公司基本面之间的相关关系。文中选取2003年至2005年沪市和深市部分上市公司为研究对象,运用一元和多元回归分析。考察了财务杠杆与净资产收益率、每股收益、总资产收益率、Tobin’s Q值的相关性。