Asymptotics in adaptive cluster sampling

In this article we consider asymptotic properties of the Horvitz-Thompson and Hansen-Hurwitz types of estimators under the adaptive cluster sampling variants obtained by selecting the initial sample by simple random sampling without replacement and by unequal probability sampling with replacement. We develop an asymptotic framework, which basically assumes that the number of units in the initial sample, as well as the number of units and networks in the population tend to infinity, but that the network sizes are bounded. Using this framework we prove that under each of the two variants of adaptive sampling above mentioned, both the Horvitz-Thompson and Hansen-Hurwitz types of estimators are design-consistent and asymptotically normally distributed. In addition we show that the ordinary estimators of their variances are also design-consistent estimators.     

Adaptive two-stage one-per-stratum sampling

We briefly describe adaptive cluster sampling designs in which the initial sample is taken according to a Markov chain one-per-stratum design (Breidt, 1995) and one or more secondary samples are taken within strata if units in the initial sample satisfy a given condition C. An empirical study of the behavior of the estimation procedure is conducted for three small artificial populations for which adaptive sampling is appropriate. The specific sampling strategy used in the empirical study was a single random-start systematic sample with predefined systematic samples within strata when the initially sampled unit in that stratum satisfies C. The bias of the Horvitz-Thompson estimator for this design is usually very small when adaptive sampling is conducted in a population for which it is suited. In addition, we compare the behavior of several alternative estimators of the standard error of the Horvitz-Thompson estimator of the population total. The best estimator of the standard error is population-dependent but it is not unreasonable to use the Horvitz-Thompson estimator of the variance. Unfortunately, the distribution of the estimator is highly skewed hence the usual approach of constructing confidence intervals assuming normality cannot be used here.     

Estimating the Effect of Protected Lands on the Development and Conservation of Their Surroundings

Abstract:  The fate of private lands is widely seen as key to the fate of biodiversity in much of the world. Organizations that work to protect biodiversity on private lands often hope that conservation actions on one piece of land will leverage the actions of surrounding landowners. Few researchers have, however, examined whether protected lands do in fact encourage land conservation nearby or how protected lands affect development in the surrounding landscape. Using spatiotemporal data sets on land cover and land protection for three sites (western North Carolina, central Massachusetts, and central Arizona), we examined whether the existence of a protected area correlates with an increased rate of nearby land conservation or a decreased rate of nearby land development. At all sites, newly protected conservation areas tended to cluster close to preexisting protected areas. This may imply that the geography of contemporary conservation actions is influenced by past decisions on land protection, often made for reasons far removed from concerns about biodiversity. On the other hand, we found no evidence that proximity to protected areas correlates with a reduced rate of nearby land development. Indeed, on two of our three sites the development rate was significantly greater in regions with more protected land. This suggests that each conservation action should be justified and valued largely for what is protected on the targeted land, without much hope of broader conservation leverage effects.     

基于等维新息灰色马尔科夫的地铁客流量预测*

为准确预测地铁客流量的发展趋势,采用等维新息灰色GM（1,1）预测模型与马尔科夫模型相结合的方式建立等维新息灰色马尔科夫模型,探讨等维新息灰色马尔科夫模型在地铁客流量预测领域的应用;运用平均相对误差、后验差比值和小误差概率3种指标对模型精度进行检验。结果表明:等维新息灰色马尔科夫模型与原始数列的拟合程度较高,预测精度等级为Ⅰ级（优）,优于传统灰色GM(1,1)模型和等维新息灰色GM(1,1)模型的预测精度,更加符合地铁客流的实际情况。     

人工快渗的强化预处理研究

通过室内实验并结合实际工程研究了一种新型组合式人工快渗系统处理氨氮负荷较高的污水。结果表明,简易曝气装置有效降低了人工快渗池的污染物负荷,保障了整个系统的出水水质。实际工程中,经过简易曝气池的预处理,人工快渗池的水力负荷可达2.5 m/d,降低了人工快渗系统的占地面积,出水COD、氨氮、总氮等指标达到了《城镇污水处理厂污染物排放标准》(GB/T18918-2002)一级A排放标准。     

Modelling Replicated Weed Growth Data using Spatially-varying Growth Curves

Weed growth in agricultural fields constitutes a major deterrent to the growth of crops, often resulting in low productivity and huge losses for the farmers. Therefore, proper understanding of patterns in weed growth is vital to agricultural research. Recent advances in Geographical Information Systems (GIS) now allow geocoding of agricultural data, which enable more sophisticated spatial analysis. Our current application concerns the development of statistical models for conducting spatial analysis of growth patterns in weeds. Our data comes from an experiment conducted in Waseca, Minnesota, that recorded growth of the weed Setariaspp. We capture the spatial variation in Setaria spp. growth using spatially-varying growth curves. An added challenge is that these designs are spatially replicated, with each plot being a lattice of sub-plots. Therefore, spatial variation may exist at different resolutions – a macro level variation between the plots and micro level variation between the sub-plots nested within each plot. We develop a Bayesian hierarchical framework for this setting. Flexible classes of models result which are fitted using simulation-based methods.     

Adjusted two-stage adaptive cluster sampling

An adjusted two-stage sampling procedure is discussed for adaptive cluster sampling where some networks are large and others are small. A two-stage sample is drawn from the large networks and a single-stage sample is drawn from the rest. The simple random sampling (SRS) procedure without replacement is used at the initial stage. An estimator for the population mean along with its properties is discussed.     

基于灰色-马尔可夫藕合模型的区域建设用地需求预测

建设用地需求的中长期准确预测是当前土地资源规划和利用的重点和难点。本文将灰色和马尔可夫两种预测模型相结合,建立灰色-马尔可夫藕合模型,以广东省揭阳市为例,对1997到2010年间主要建设用地规模进行了需求预测,同时与其它几种常规的预测方法进行了比较。结果表明,人文驱动力相关预测法误差相对较大,其中国内生产总值(GDP)相关法准确度要优于人口相关法。趋势线法计算简单,预测准确度也相对较高,但只适于短期预测。灰色预测法精确度较高,计算需要模型的支持、专业性强。灰色-马尔可夫预测法由于是对灰色预测的偏离值进行了纠正,因而准确度最高。尽管该方法需要大量数据的支持,计算量大,但仍是值得推荐的高准确度的区域建设用地的专业预测方法。     

实施简易工况法排气检测若干问题探讨

国标GB18285-2005和GB3847-2005规定在用机动车的排气检测方法选择与简易工况法标准限值的制定均由地方根据实际情况确定,虽增强了地方排气监管工作灵活性,但困难也增加了.各地在推动实施简易工况法时,检测方法的选择应重点从地方管理、地方经济、技术条件和机动车排气监督管理发展方向进行综合考虑,条件许可的地方选用简易瞬态工况法.简易工况法的初始标准限值可以先选用HJ/T 240-2005和HJ/T241-2005两个行业标准中的最松限值,然后在推进简易工况法的过程中逐步收集检测数据,并重新确定地方的排放限值.     

简化活性污泥数学模型的优化

为了从控制运行的角度促进简化数学模型的应用，必须借助其它优化手段进一步提高预测精度。本文主要介绍了应用于简化数学模型的扩展卡尔曼滤波、神经网络和误差反馈系统三种优化方法以及优化后的验证结果。从验证结果来看，优化的ROM模型与ASMl模型的定性变化行为相似，基于神经网络的复合模型对PO4^3-和NOx^-的预测结果非常准确，误差反馈的优化系统模拟性能良好。