Relationships between landscape patterns and ecological processes can vary with changing resolution. Many studies in ecosystem services and human health rely on spatial-dependent data, yet the effects of changes in spatial resolution on the linkages between landscape and human health are underexplored. This study seeks to address the research gap by exploring the relationships of green land cover and pattern metrics at 1 m, 10 m, and 30 m with life expectancy in the City of Baltimore, Maryland, USA. Spearman’s rho correlation and stepwise and hierarchical regression models were applied. Results showed that the effects of resolution change did not emerge for percent green land cover but were evident in other pattern metrics. Multivariate relationships showed that metrics at 1 m explained the most variability of the relationships between green land cover and life expectancy after controlling for potential confounding factors (adjusted R2?=?0.776, and 0.752 at 10 m and 0.747 at 30 m). Edge density of coarse vegetation was significantly associated with life expectancy at 1 m (adjusted odds ratio [AOR]?=?1.012, 95%CI?=?1.004–1.024, p?<?0.01) and 10 m (AOR?=?1.018, 95%CI?=?1.009–1.027, p?<?0.001) but not at 30 m. Euclidean distance of fine vegetation had a strong positive association with greater life expectancy at 1 m (AOR?=?2.067, 95%CI?=?1.185–4.072, p?<?0.05) but not at 10 m and 30 m. These findings underscore the importance of acknowledging the effects of resolution on the interpretation of landscape-human health relationships and the need for caution when results are used in planning and management decisions.
In this paper, we use the Bayesian method in the application of hypothesis testing and model selection to determine the order of a Markov chain. The criteria used are based on Bayes factors with noninformative priors. Com¬parisons with the commonly used AIC and BIC criteria are made through an example and computer simulations. The results show that the proposed method is better than the AIC and BIC criteria, especially for Markov chains with higher orders and larger state spaces. 相似文献
The continuous quadratic variation of asset return plays a critical role for high-frequency trading. However, the microstructure noise could bias the estimation of the continuous quadratic variation. Zhang et al. (2005Zhang, L., Mykland, P., Ait-Sahalia, Y. (2005). A tale of two time scales: determining integrated volatility with noisy high-frequency data. J. Amer. Statist. Assoc. 100(472):1394–1411.[Taylor & Francis Online], [Web of Science ®], [Google Scholar]) proposed a batch estimator for the continuous quadratic variation of high-frequency data in the presence of microstructure noise. It gives the estimates after all the data arrive. This article proposes a recursive version of their estimator that outputs variation estimates as the data arrive. Our estimator gives excellent estimates well before all the data arrive. Both real high-frequency futures data and simulation data confirm the performance of the recursive estimator. 相似文献
Degradation models are widely used these days to assess the lifetime information of highly reliable products if there exist some quality characteristics (QC) whose degradation over time can be related to the reliability of the product. In this study, motivated by a laser data, we investigate the mis-specification effect on the prediction of product's MTTF (mean-time-to-failure) when the degradation model is wrongly fitted. More specifically, we derive an expression for the asymptotic distribution of quasi-MLE (QMLE) of the product's MTTF when the true model comes from gamma degradation process, but is wrongly assumed to be Wiener degradation process. The penalty for the model mis-specification can then be addressed sequentially. The result demonstrates that the effect on the accuracy of the product's MTTF prediction strongly depends on the ratio of critical value to the scale parameter of the gamma degradation process. The effects on the precision of the product's MTTF prediction are observed to be serious when the shape and scale parameters of the gamma degradation process are large. We then carry out a simulation study to evaluate the penalty of the model mis-specification, using which we show that the simulation results are quite close to the theoretical ones even when the sample size and termination time are not large. For the reverse mis-specification problem, i.e., when the true degradation is a Wiener process, but is wrongly assumed to be a gamma degradation process, we carry out a Monte Carlo simulation study to examine the effect of the corresponding model mis-specification. The obtained results reveal that the effect of this model mis-specification is negligible. 相似文献
Although the bivariate normal distribution is frequently employed in the development of screening models, the formulae for computing bivariate normal probabilities are quite complicated. A simple and accurate error-bounded, noniterative approximation for bivariate normal probabilities based on a simple univariate normal quadratic or cubic approximation is developed for use in screening applications. The approximation, which is most accurate for large absolute correlation coefficients, is especially suitable for screening applications (e.g., in quality control), where large absolute correlations between performance and screening variables are desired. A special approximation for conditional bivariate normal probabilities is also provided which in quality control screening applications improves the accuracy of estimating the average outgoing product quality. Some anomalies in computing conditional bivariate normal probabilities using BNRDF and NORDF in IMSL are also discussed. 相似文献
Zero inflated Poisson regression is a model commonly used to analyze data with excessive zeros. Although many models have been developed to fit zero-inflated data, most of them strongly depend on the special features of the individual data. For example, there is a need for new models when dealing with truncated and inflated data. In this paper, we propose a new model that is sufficiently flexible to model inflation and truncation simultaneously, and which is a mixture of a multinomial logistic and a truncated Poisson regression, in which the multinomial logistic component models the occurrence of excessive counts. The truncated Poisson regression models the counts that are assumed to follow a truncated Poisson distribution. The performance of our proposed model is evaluated through simulation studies, and our model is found to have the smallest mean absolute error and best model fit. In the empirical example, the data are truncated with inflated values of zero and fourteen, and the results show that our model has a better fit than the other competing models. 相似文献
Deriving from Parasite Single proposed by Yamada (1997), parasites in this study is redefined as those who live with and financially rely on their parents in terms of living expenses after school graduation. The current study adopts the logit model and utilizes the data from the 1999 to 2000 Taiwan Panel Study of Family Dynamics to investigate the determinants of parasites. The finding reveals that gender, age, marital status, and the value of filial piety are significantly different between parasites and non-parasites. Moreover, gender, monthly income, age and marital status are determinants of the probability of being parasites. 相似文献