Comparing spatially varying coefficient models: a case study examining violent crime rates and their relationships to alcohol outlets and illegal drug arrests

In this paper, we compare and contrast a Bayesian spatially varying coefficient process (SVCP) model with a geographically weighted regression (GWR) model for the estimation of the potentially spatially varying regression effects of alcohol outlets and illegal drug activity on violent crime in Houston, Texas. In addition, we focus on the inherent coefficient shrinkage properties of the Bayesian SVCP model as a way to address increased coefficient variance that follows from collinearity in GWR models. We outline the advantages of the Bayesian model in terms of reducing inflated coefficient variance, enhanced model flexibility, and more formal measuring of model uncertainty for prediction. We find spatially varying effects for alcohol outlets and drug violations, but the amount of variation depends on the type of model used. For the Bayesian model, this variation is controllable through the amount of prior influence placed on the variance of the coefficients. For example, the spatial pattern of coefficients is similar for the GWR and Bayesian models when a relatively large prior variance is used in the Bayesian model.      

Econometric analysis of the ship demolition market

The topic of ship recycling has obtained considerable attention during the last two decades for a variety of reasons with the likelihood of the adoption of a new international convention under the auspices of the International Maritime Organization (IMO). This study applies econometric modeling to a unique data set to provide insight into the dynamics of the ship recycling market. The data set contains information on 51,112 ships over 100 gt and includes 748,621 events over a period of 29 years. The analysis confirms a negative relationship of earnings and a positive relationship of scrap prices for all locations while Bangladesh seems to be more sensitive to changes in earnings than the other locations and more likely demolishes larger and older vessels. The results for flag and ownership vary across scrapping locations with Malta and Cyprus indicating potential importance from a registry perspective. The overall safety profile of a vessel seems to be less important towards the probability of a ship being scrapped. Possible implementation of the convention at EU level will mostly likely affect Turkey while non-ratification of one of the major flags will most likely affect China or Bangladesh.     

Evaluation of Inference Adequacy in Cumulative Logistic Regression Models: An Empirical Validation of ISWRidge Relationships

Internal solitary wave propagation over a submarine ridge results in energy dissipation, in which the hydrodynamic interaction between a wave and ridge affects marine environment. This study analyzes the effects of ridge height and potential energy during wave-ridge interaction with a binary and cumulative logistic regression model. In testing the Global Null Hypothesis, all values are p 〈0.001, with three statistical methods, such as Likelihood Ratio, Score, and Wald. While comparing with two kinds of models, tests values obtained by cumulative logistic regression models are better than those by binary logistic regression models. Although this study employed cumulative logistic regression model, three probability functions p^1, p^2 and p^3, are utilized for investigating the weighted influence of factors on wave reflection. Deviance and Pearson tests are applied to cheek the goodness-of-fit of the proposed model. The analytical results demonstrated that both ridge height （X1 ） and potential energy （X2 ） significantly impact （p 〈 0. 0001 ） the amplitude-based refleeted rate; the P-values for the deviance and Pearson are all 〉 0.05 （0.2839, 0.3438, respectively）. That is, the goodness-of-fit between ridge height （ X1 ） and potential energy （X2） can further predict parameters under the scenario of the best parsimonious model. Investigation of 6 predictive powers （ R2, Max-rescaled R^2, Sorners＇ D, Gamma, Tau-a, and c, respectively） indicate that these predictive estimates of the proposed model have better predictive ability than ridge height alone, and are very similar to the interaction of ridge height and potential energy. It can be concluded that the goodness-of-fit and prediction ability of the cumulative logistic regression model are better than that of the binary logistic regression model.     

Evaluation of Inference Adequacy in Cumulative Logistic Regression Models： An Empirical Validation of ISW-Ridge Relationships

Internal solitary wave propagation over a submarine ridge results in energy dissipation, in which the hydrodynamic interaction between a wave and ridge affects marine environment. This study analyzes the effects of ridge height and potential energy during wave-ridge interaction with a binary and cumulative logistic regression model. In testing the Global Null Hypothesis, all values are p<0.001, with three statistical methods, such as Likelihood Ratio, Score, and Wald. While comparing with two kinds of models, tests values obtained by cumulative logistic regression models are better than those by binary logistic regression models. Although this study employed cumulative logistic regression model, three probability functions p^1, p^2 and p^3, are utilized for investigating the weighted influence of factors on wave reflection. Deviance and Pearson tests are applied to check the goodness-of-fit of the proposed model. The analytical results demonstrated that both ridge height (X1) and potential energy (X2) significantly impact (p<0.0001) the amplitude-based reflected rate; the P-values for the deviance and Pearson are all >0.05 (0.2839, 0.3438, respectively). That is, the goodness-of-fit between ridge height (X1) and potential energy (X2) can further predict parameters under the scenario of the best parsimonious model.Investigation of 6 predictive powers (R2, Max-rescaled R2, Somers'D, Gamma, Tau-a, and c, respectively) indicate that these predictive estimates of the proposed model have better predictive ability than ridge height alone, and are very similar to the interaction of ridge height and potential energy. It can be concluded that the goodness-of-fit and prediction ability of the cumulative logistic regression model are better than that of the binary logistic regression model.     

Skeletal linear extension rates of the foliose scleractinian coral Merulina ampliata (Ellis & Solander, 1786) in a turbid environment

Skeletal linear extension rates of a foliaceous, IndoPacific, skiophilous, heterotrophic, scleractinian Merulina ampliata (Ellis & Solander 1786) were obtained along a sediment/nutrient load gradient at the southern islands of Singapore. Measurements were made during November 1999– November 2000 using the alizarin red‐S staining technique. Suspended particulate matter concentration (r²_adj = 0.76), turbidity (r²_adj = 0.59), the organic content of suspended sediments (r² = 0.50), and nitrite‐nitrate concentration (r²_adj = 0.50) were significant predictors of the skeletal linear extension rate of M. ampliata. Maximum linear extension growth rates of M. ampliata (mean ± SD: 1.43 ± 0.67–3.26 ± 0.59 cm·year^?1) were comparable to 15‐year‐old accounts at the same research sites, indicating adaptation to low‐light, high‐sediment waters.     

台风对海洋叶绿素a浓度影响的定量遥感初探

研究台风对海洋水色环境的影响,是目前海洋遥感技术又一应用领域。由于台风期间天气恶劣,遥感资料较少,国际上主要针对个别典型台风,研究其对海表温度、海洋叶绿素a浓度及初级生产力的影响,很少通过遥感资料系统地对这一影响进行定量分析和建模。自2000到2007年,过境中国近海以及西北太平洋海域台风近百次,作者通过系统地分析这期间MODIS,SeaWiFS的3A级叶绿素a浓度数据,结果发现:(1)台风促进了相应海域叶绿素a浓度的大幅增长,总体上平均增长约1.426倍,个别区域在5倍以上,同时,该增长一般延后3~6d,在7~10d后恢复到原来的水平;(2)进一步对这些数据进行一元统计线性回归,发现叶绿素a浓度增长比(R_chl-a)与台风影响因子(Tsub>w)满足如下关系:R_chl-a=0.0012Tsub>w+1.017,其相关系数达0.8;(3)台风期间叶绿素a浓度与无台风时叶绿素a浓度之间有很强的线性关系,其关系满足:C_chl-a=1.2367C_0chl-a+0.0636,且相关系数高达0.98。这一初步研究结果对进一步通过遥感手段深入研究台风对海洋水色环境的影响有借鉴意义。     

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腾格里沙漠西北缘湖泊沉积记录的全新世中期气候环境

通过腾格里沙漠西北缘青土湖沉积物粒度、有机碳、碳酸盐、碳氮比和有机质稳定同位素等多项沉积学气候代用指标及精确定年的综合分析,建立了该区域全新世中期9.0~3.0 cal.kaBP的古气候演化序列。结果表明,9~7.8 cal.kaBP期间,区域的水分条件和温度逐渐上升,植被状况好转,此阶段属于全新世早期向全新世暖湿期转变的过程;而在7.8~7.5 cal.kaBP期间出现了显著的百年尺度的干旱事件,沉积物主要以砂质沉积为主,此时湖泊生产力显著下降;全新世期间最为暖湿的气候适宜期出现在7.5~5.0 cal.kaBP;5.0 cal.kaBP以来,该区域出现了较为明显的干旱化趋势。     

15-20世纪大陆泽与宁晋泊演变的影响因素分析

15至20世纪,海河流域南系历史上著名的湖泊--大陆泽和宁晋泊经历了从宽广到干涸的巨大变迁.对于二泊演变的原因,此前学者从未做过专门的分析和研究.本文以明清时期丰富的历史文献为依据,对影响湖泊演变的各大自然和人文因子进行了深入探讨,得出如下基本结论:海河南系水系格局不断变迁导致湖泊水源补给发生迅速改变,是促使湖泊相应发生显著扩张与萎缩,并最终导致湖泊消亡的直接主要动因.此外,来自河流的泥沙淤积,气候的干湿变化,人类拦水筑坝、占垦涸泊等活动加速了湖泊的演变与消涸.     

Local and landscape effects on spatial patterns of mangrove forest during wetter and drier periods: Moreton Bay,Southeast Queensland,Australia

Land use/cover and mangrove spatial changes were assessed for ten sites and their sub-catchments in Southeast Queensland, Australia. Two time periods were involved: 1972–1990, a period of relatively high rainfall, and 1990–2004, which was significantly drier. Aerial photographs and Landsat satellite imagery were used to map the inter-tidal wetlands and classify the land use/cover in the sub-catchments. A Maximum Likelihood Classification was used to map three types of land cover: agriculture, built-up and plantation forest. Mangroves (mainly Avicennia marina) were the focus as they have been recorded over recent decades encroaching into salt marsh. The Mangrove-Salt marsh Interface (MSI) Index was developed to quantify the relative opportunity for mangroves to expand into salt marshes, based on the shared boundary between them. The index showed a consistent relationship with mangrove expansion and change. To address problems of high dimensionality and multi-collinearity of predictor variables, a Partial Least Squares Regression (PLSR) model was used. A key finding of this research was that the contribution of environmental variables to spatial changes in the mangroves was altered following a reduction in rainfall. For example, agriculture had more influence on mangrove expansion and change during the wet period than during the dry period.