Bayesian ratemaking procedure of crop insurance contracts with skewed distribution

Over the years, crop insurance programs became the focus of agricultural policy in the USA, Spain, Mexico, and more recently in Brazil. Given the increasing interest in insurance, accurate calculation of the premium rate is of great importance. We address the crop-yield distribution issue and its implications in pricing an insurance contract considering the dynamic structure of the data and incorporating the spatial correlation in the Hierarchical Bayesian framework. Results show that empirical (insurers) rates are higher in low risk areas and lower in high risk areas. Such methodological improvement is primarily important in situations of limited data.     

Variable selection in spatial regression via penalized least squares

We consider variable selection in linear regression of geostatistical data that arise often in environmental and ecological studies. A penalized least squares procedure is studied for simultaneous variable selection and parameter estimation. Various penalty functions are considered including smoothly clipped absolute deviation. Asymptotic properties of penalized least squares estimates, particularly the oracle properties, are established, under suitable regularity conditions imposed on a random field model for the error process. Moreover, computationally feasible algorithms are proposed for estimating regression coefficients and their standard errors. Finite‐sample properties of the proposed methods are investigated in a simulation study and comparison is made among different penalty functions. The methods are illustrated by an ecological dataset of landcover in Wisconsin. The Canadian Journal of Statistics 37: 607–624; 2009 © 2009 Statistical Society of Canada     

西汉时期我国人口分布空间格局及其成因探讨

在数字化西汉地图的基础上,结合西汉人口数据,运用GIS软件完成西汉时期人口密度分布和分级图。得出西汉时期我国人口分布空间格局是人口多集中于黄河中下游地区,南方人口较稀少的结论。并在此基础上对其成因进行探讨,西汉时期人口分布的空间格局是在自然因素、政治因素和历史因素的共同作用下形成的。     

西方居住隔离理论:发展历程与现实启示

自恩格斯首次揭示不同群体的居住隔离状态以来,西方社会学经济学等相关学科先后形成了三种不同取向的居住隔离理论,即强调不同人群空间分离的人文区位学居住分异理论,强调住宅更替规律的住房过滤理论,以及强调住宅阶级的新都市社会学居住隔离理论。这些理论共同提醒人们,在当代中国的城镇发展和住房建设中,必须有效预防居住空间隔离,阻止不同社会群体和阶层之间的隔离和对抗。     

国际旅游客流空间移动规律研究

国际旅游客流的空间移动呈现一定的规律性,其主流在发达国家之间移动,以短程移动居主导地位,且互动效应明显.从流向上看,国际旅游客流由北向南移动,由内陆向沿海地区及其岛屿移动.     

空间性语言、空间语法和中国古代诗歌的空间性——从言、象、意论中国古代诗学的空间性之一

文学艺术是语言的艺术,因而从语言文字的角度来探讨中国古代诗歌艺术是诗学研究的应有之义。而作为创作媒介的汉语,由于自身是种空间性语言以及其语法的空间性,则必然使得中国古代诗歌艺术具有空间性的特性。     

基于势能模型的我国省会城市经济影响区的划分

城市经济影响区现已成为城市发展所密切关注的焦点。运用势能模型划分我国31个省会城市的经济影响区,并概括它们的总体分布特征;研究各省区的经济影响区构成情况和各经济影响区的跨省分布情况;将省会城市经济影响区与省域行政范围进行叠合分析,得出两者间的4种空间关系。     

京津冀县域尺度碳排放时空演变特征——基于DMSP/OLS夜间灯光数据

以全球DMSP/OLS夜间灯光数据为基础,通过影像重投影、相互校正、年内校正、时间序列校正后,得到京津冀地区校正后DMSP/OLS夜间灯光数据;利用京津冀能源消费统计数据和碳排放因子数据,计算得出京津冀地区分省市碳排放量。在此基础上,通过数据拟合构建京津冀县域尺度碳排放估算模型,估算模型拟合优度为0.975 2,估算模型有效。利用构建的估算模型对京津冀县域尺度碳排放量进行估算,并采用探索性空间数据分析方法对京津冀县域尺度碳排放时空演变特征进行分析。结果表明：2000—2013年京津冀县域尺度碳排放呈现快速增长特征,且存在显著的区域差异,高碳县域表现为“Y形”分布特征。县域尺度碳排放具有显著空间正相关性,碳排放空间相关性呈不断减弱的趋势,且呈现空间高值集聚效应和空间低值集聚效应。热点与次热点区域集中在北京市、天津市以及与北京市、天津市邻近的河北省区域;冷点与次冷点区域包括承德西北部地区和河北省中南部地区。     

Fast bandwidth selection for estimation of the pair correlation function

ABSTRACT

Kernel estimation is a popular approach to estimation of the pair correlation function which is a fundamental spatial point process characteristic. Least squares cross validation was suggested by Guan [A least-squares cross-validation bandwidth selection approach in pair correlation function estimations. Statist Probab Lett. 2007;77(18):1722–1729] as a data-driven approach to select the kernel bandwidth. The method can, however, be computationally demanding for large point pattern data sets. We suggest a modified least squares cross validation approach that is asymptotically equivalent to the one proposed by Guan but is computationally much faster.     

Functional regression concurrent model with spatially correlated errors: application to rainfall ground validation

In this paper, we give an extension of the functional regression concurrent model to the case of spatially correlated errors. We propose estimating the spatial correlation structure by using functional geostatistics. The estimation of the regression parameters is carried out by feasible generalized least squares. This modeling approach is motivated by the problem of validating rainfall data retrieved from satellite sensors. In this sense, we use the methodology to study the relationship between satellite and ground rainfall time series recorded in 82 weather stations from Department of Valle del Cauca, Colombia. The model obtained allows predicting pentadal rainfall curves in many sites of the region of interest by using as input the satellite information. A residual analysis shows a good performance of the methodology proposed.