Actions and policies to enhance biodiversity in the urban landscape must match the spatial scale at which biodiversity responds to the management and target variables. To this end, we compare the importance and effect of different kinds of greenery cover and road-lane density on bird and butterfly species richness between two landscape scales: 50-m versus 126-m radii around point counts (equivalent to areas of 0.8 h and 5 ha, respectively). We also compared the results against those of an earlier study using 500-m walking transects with widths of 100 m (i.e., 5 ha). Road lane density was more important at the 126-m than 50-m radius for both birds and butterflies. For birds, natural vegetation or forest cover and cultivated shrub cover were also more important at 126-m radius whereas the cultivated tree canopy cover was more important at 50-m radius. Cultivated tree cover and natural vegetation or forest cover were positively associated with species richness while road lane density and cultivated shrub cover were negatively associated with species richness. The results from point counts generally corroborate the results from the transects-based study, except that the short-duration point counts performed poorly in sampling butterflies. Our results indicate that in designing urban greenery policy, the plot sizes of individual developments is an appropriate spatial scale for the stipulation of tree cover targets, while urban planners have more flexibility to allocate natural greenery at broader spatial scales.
The accelerated failure time (AFT) model is an important regression tool to study the association between failure time and covariates. In this paper, we propose a robust weighted generalized M (GM) estimation for the AFT model with right-censored data by appropriately using the Kaplan–Meier weights in the GM–type objective function to estimate the regression coefficients and scale parameter simultaneously. This estimation method is computationally simple and can be implemented with existing software. Asymptotic properties including the root-n consistency and asymptotic normality are established for the resulting estimator under suitable conditions. We further show that the method can be readily extended to handle a class of nonlinear AFT models. Simulation results demonstrate satisfactory finite sample performance of the proposed estimator. The practical utility of the method is illustrated by a real data example. 相似文献
We study whether priors that admit full surplus extraction (FSE) are generic, an issue that becomes a gauge to evaluate the validity of the current mechanism design paradigm. We consider the space of priors on the universal type space, and thereby relax the assumption of a fixed finite number of types made by Crémer and McLean (1988). We show that FSE priors are topologically generic, contrary to the result of Heifetz and Neeman (2006) that FSE is generically impossible, both geometrically and measure‐theoretically. Instead of using the BDP approach or convex combinations of priors adopted in Heifetz and Neeman (2006), we prove our genericity results by showing a robustness property of Crémer–McLean mechanisms. 相似文献
Social Indicators Research - Social norms are essential but vary across human societies. With the internationalization of human society, the population’s mobility has greatly increased, which... 相似文献
AbstractPartially linear models attract much attention to investigate the association between predictors and the response variable when the dependency on some predictors may be nonlinear. However, the hypothesis test for significance of predictors is still challenging, especially when the number of predictors is larger than sample size. In this paper, we reconsider the test procedure of Zhong and Chen (2011Zhong, P., and S. Chen. 2011. Tests for high-dimensional regression coefficients with factorial designs. Journal of the American Statistical Association 106 (493):260–74. doi:10.1198/jasa.2011.tm10284.[Taylor & Francis Online], [Web of Science ®], [Google Scholar]) when regression models have nonlinear components, and propose a generalized U-statistic for testing the linear components of the high dimensional partially linear models. The asymptotic properties of test statistic are obtained under null and alternative hypotheses, where the effect of nonlinear components should be considered and thus is different from that in linear models. Through simulation studies, we demonstrate good finite-sample performance of the proposed test in comparison with the existing methods. The practical utility of our proposed method is illustrated by a real data example. 相似文献