EGM96与EGM2008大地水准面模型拟合精度分析

在Trimble Business Center(TBC)软件中分别加载EGM96与EGM2008两种大地水准面模型,通过观测的GPS静态数据,固定一个GPS控制点的水准高程,计算出各点的拟合高程,与四等水准成果进行对比,结果表明EGM2008大地水准面模型精度优于EGM96大地水准面模型。     

GPS高程拟合在带状地形测量中的应用

如何高精度地将GPS大地高转换为正常高是地形测量中的研究重点。在某地形测量项目中,根据水准测量数据,使用EGM2008地球重力场模型,选择部分GPS/水准控制点进行GPS高程拟合,将GPS大地高转换为正常高。精度检核结果表明,该方法使用较少的GPS/水准控制点拟合就能满足图根控制点高程精度要求,可以减少水准测量工作量,提高地形测量工作效率。     

GPS水准代替三等水准测量技术应用研究

GPS定位在水准测量方面，因为大地水准面和参考椭球面之间的位置关系非常复杂，用GPS高程代替三等水准往往达不到好的效果，本文通过建立GPS高程异常模型，利用GPS水准点进行参数求解，粗差检验，结合工程实例与三等水准测量精度比较，论证了应用可行性。     

GPS在机场高程测量中的应用

本文以JX机场GPs定位测量数据并结合水准测量数据。探讨GPs点的水准高程计算方法。采用曲面拟合法处理已知的公共点的水准高程。从而推求其余GPS点的水准高程。计算结果表明。对于局部平坦地区，高程异常变化有规律时。采用曲面拟合能够得到满意的结果。     

通过实例进行GPS水准精度分析

<正>在工程的实际应用中选定若干水准点,在这些点上进行GPS观测,建立拟合基准面高程系统,并以某一点的高程为起算高程,可以说也是一种独立的高程系统,与在传统的独立水准网中,以某一水准点高程为起算高程,或任意假定一个点的高程为起算高程的情况是类似的。在实用上,GPS点在此系统中的高程精度与GPS点大地高的精度相同,采用水准测量加密一些点的高程的精度除受水准高差观测精度的影响外,还受到由于水准面与拟合面差异的影响。为了研究建立GPS水准测量与几何水准测量之间的拟合数学模型,结合生产实际,我们在霍煤炭素项目控制网测量中对GPS拟合高程作了实验,也在多条公路测量中进行验证和比较,取得了一定量的数据及可靠的实验成果。     

GPS高程拟合在像片控制测量中的应用

GPS高程拟合是指在范围不大的区域内，高程异常具有一定的几何相关性这一原理，采用数学方法求解正高，正常高和高程异常。在规定的技术指标内，满足项目设计要求、数字化内业生产要求的同时制定出若干个GPS拟合工作区域，通过分解成小的拟合区域来降低高程异常带来的影响。根据各区域地形情况设计不同的GPS拟合控制网，因网而异选择多个合适的参考站，参考站一般采用水准点上布设GPS点或对GPS点进行水准联测的方法来实现，本次实验选择了后者，拟合网内最弱点应用水准测量施测检测。应用静态GPS拟合高程替代等外水准测量，解决水准测量中受地形空间等因素限制的困难，减少外业工作量，提高了工作效率，减少了人力物力的投入，降低了生产作业成本。     

多面函数法在GPS高程拟合中的应用

为了改善GP5大地高向正常高转换的精度，在局部区域内，建立多面函数模型进行高程拟合．可以达到较高的精度。文中利用多面函数模型进行高程拟合，除选取分布均匀的GPS水准联测点外，还对核函数形式的选取做了详细地分析，并与高程拟合中常用的二次曲面拟合法做了对比，进行了精度分析。     

宁夏红寺堡开发区工程控制网的建立

红寺堡开发区工程控制网包括三等GPS控制网和四等水准网,本文表述了为提高平面精度采用的数据处理方法和达到的精度指标,提出了对平面网起算点进行内符精度检测;采用已知GPS水准点对红寺堡区域精化大地水准面进行精度检验,验证红寺堡区域精化大地水准面高程拟合的精度等级。     

宁夏红寺堡开发区工程控制网的建立

红寺堡开发区工程控制网包括三等GPS控制网和四等水准网,本文表述了为提高平面精度采用的数据处理方法和达到的精度指标,提出了对平面网起算点进行内符精度检测;采用已知GPs水准点对红寺堡区域精化大地水准面进行精度检验,验证红寺堡区域精化大地水准面高程拟合的精度等级.     

小议GPS高程测量拟合若干探讨

利用大地水准面的原理和方法对CPS测高程与水准测量理论进行了论证分析,提出了采用极少数量的GPS与水准重合点将GPS大地高直接转换为具有厘米量级的方式与方法。     

A general endogenous grid method for multi-dimensional models with non-convexities and constraints

The endogenous grid method (EGM) significantly speeds up the solution of stochastic dynamic programming problems by simplifying or completely eliminating root-finding. We propose a general and parsimonious EGM extended to handle (1) multiple continuous states and choices, (2) multiple occasionally binding constraints, and (3) non-convexities such as discrete choices. Our method enjoys the speed gains of the original one-dimensional EGM, while avoiding expensive interpolation on multi-dimensional irregular endogenous grids. We explicitly define a broad class of models for which our solution method is applicable, and illustrate its speed and accuracy using a consumption–saving model with both liquid assets and illiquid pension assets and a discrete retirement choice.     

Solving Models with Jump Discontinuities in Policy Functions

We compare global methods for solving models with jump discontinuities in the policy function. We find that differences between value function iteration (VFI) and other methods are economically significant and Euler equation errors fail to be a sufficient measure of accuracy in such models. VFI fails to accurately identify both the location and size of jump discontinuities, while the endogenous grid method (EGM) and the finite element method (FEM) are much better at approximating this class of models. We further show that combining VFI with a local interpolation step (VFI‐INT) is sufficient to obtain accurate approximations. The combination of computational speed, relatively easy implementation and adaptability make VFI‐INT especially suitable for approximating models with jump discontinuities in policy functions: while EGM is the fastest method, it is relatively complex to implement; implementation of VFI‐INT is relatively straightforward and it is much faster than FEM.     

Nowcasting in real time using popularity priors

We construct a “Google Recession Index” (GRI) using Google Trends data on internet search popularity, which tracks the public’s attention to recession-related keywords in real time. We then compare nowcasts made with and without this index using both a standard dynamic factor model and a Bayesian approach with alternative prior setups. Our results indicate that using the Bayesian model with GRI-based “popularity priors,” we could identify the 2008Q3 turning point in real time, without sacrificing the accuracy of the nowcasts over the rest of the sample periods.     

FAIR TRADE IS COUNTERPRODUCTIVE AND UNFAIR: REJOINDER

This is a rejoinder to a criticism of Henderson (2008 ) by Alastair Smith. Our conclusion is that Henderson's basic case, although nicked around the edges by developments since the original was written, still stands. Moreover, we point out that Smith's criticism of Henderson's point that Fair Trade could help kill the banana actually supports Henderson's case. Finally, Smith's proposed 'trade, not aid' solution does not contradict Henderson (2008 ). Refusing to buy Fair Trade coffee and other products and, instead, buying quality coffee and other products would not reduce trade, as Smith seems to imply.     

Markov体制转换模型与经济周期分析

根据信息选择滞后准则,将经济增长率的特点状态分为两个。本模型的特点是引入一个虚拟变量将序列在两个状态下的均值再分为改革开放前后两个情况。根据经济增长率的平滑概率发现改革开放前周期与波峰和波谷划分的周期相同,改革开放后的周期基本相同,只是经济的收缩状态比较长,尤其近几年。模型估计收缩的持续时间是3.5年,扩张的持续时间是3.1年;2005年和2006年是经济发展的扩张期,预计2007年是扩张期,2008年在北京举办奥运会,是经济发展的高峰期,预计2009年可能是经济从扩张到收缩的转折期,2010年经济有恢复的迹象。     

核电中国专利分析

文章从统计分析的角度,对近20年来核电中国专利进行数据挖掘与分析,了解了该产业在我国的申请、技术领域分布等总体发展情况。分析结果显示,核电专利申请和授权量存在一定程度的时间和地区"集聚"现象。2008年以来,核电中国专利申请与授权进入高峰期,从地域来看,上海、广东、江苏授权核电专利占据国内授权核电专利的半壁江山,在核电发展方面比其它地区具有技术上的优势。     

“The weighted average cost of capital is not quite right”: A rejoinder

Richard Miller's reply (2008) to my comment (2008) on his claim (2007) that the standard WACC formula fails to correctly remunerate shareholders and bondholders raises crucial questions on the nature of the project's debt that he considers in his calculations. To clarify this point, I here introduce several possible definitions of a loan associated with a project, and discuss their respective relevance for a WACC calculation. In addition, Mr. Miller's suggestion that the standard WACC formula is not quite right remains unsubstantiated.     

戴尔猛攻中国

在中国市场的复杂格局及游戏规则面前，急欲变革的戴尔具备了相应的决心、耐心以及技巧吗？     

Predicting equity premium using dynamic model averaging. Does the state–space representation matter?

Dynamic model averaging (DMA) has become a very useful tool with regards to dealing with two important aspects of time-series analysis, namely, parameter instability and model uncertainty. An important component of DMA is the Kalman filter. It is used to filter out the latent time-varying regression coefficients of the predictive regression of interest, and produce the model predictive likelihood, which is needed to construct the probability of each model in the model set. To apply the Kalman filter, one must write the model of interest in linear state–space form. In this study, we demonstrate that the state–space representation has implications on out-of-sample prediction performance, and the degree of shrinkage. Using Monte Carlo simulations as well as financial data at different sampling frequencies, we document that the way in which the current literature tends to formulate the candidate time-varying parameter predictive regression in linear state–space form ignores empirical features that are often present in the data at hand, namely, predictor persistence and predictor endogeneity. We suggest a straightforward way to account for these features in the DMA setting. Results using the widely applied Goyal and Welch (2008) dataset document that modifying the DMA framework as we suggest has a bearing on equity premium point prediction performance from a statistical as well as an economic viewpoint.     

Local Adaptive Multiplicative Error Models for High‐Frequency Forecasts

We propose a local adaptive multiplicative error model (MEM) accommodating time‐varying parameters. MEM parameters are adaptively estimated based on a sequential testing procedure. A data‐driven optimal length of local windows is selected, yielding adaptive forecasts at each point in time. Analysing 1‐minute cumulative trading volumes of five large NASDAQ stocks in 2008, we show that local windows of approximately 3 to 4 hours are reasonable to capture parameter variations while balancing modelling bias and estimation (in)efficiency. In forecasting, the proposed adaptive approach significantly outperforms a MEM where local estimation windows are fixed on an ad hoc basis. Copyright © 2014 John Wiley & Sons, Ltd.