Extended Abstract. Inferences for spatial data are affected substantially by the spatial configuration of the network of sites where measurements are taken. Consider the following standard data-model framework for spatial data. Suppose a continuous, spatially-varying quantity, Z, is to be observed at a predetermined number, n, of points ....[ To Countinue Click here]

Spatial mobility is a topical concept of analytical migration science, which makes it possible to assess the desires, readiness and capabilities of the population to move over certain distances and time. In the management of spatial mobility assessment requires the organization of systematic monitoring, which includes identifying the mobility potential in spatial and temporal interpretation, th...

estimating the amount of variation due to spatial dependence at different scales provides a basis for designing effective experiments. accurate knowledge of spatial structures is needed to inform silvicultural guidelines and management decisions for long term sustainability of forests. furthermore, geostatistics is a useful tool to describe and draw map the spatial variability and estimation of...

the objective of this study was to determine the effects of different heel heights on selected gait parameters in a sample of young nigerian females. a purposive sample of eighty apparently healthy undergraduates of nnamdi azikiwe university, nnewi campus participated in the study. their mean age, height, and weight were 21.98± 1.83 years, 1.65±0.06 meters, 59.50±9.34 kilograms respectively. an...

objective(s) the brief interruption of cerebral blood flow causes permanent brain damage and behavioral dysfunction. the hippocampus is highly vulnerable to ischemic insults, particularly the ca1 pyramidal cell layer. there is no effective pharmacological strategy for improving brain tissue damage induced by cerebral ischemia. previous studies reported that pentoxifylline (ptx) has a neuroprote...

Covariance functions and variograms play a fundamental role in exploratory analysis and statistical modelling of spatial and spatio-temporal datasets. In this paper, we construct a new class of spatial covariance functions using the Fourier transform of some higher-order kernels. Moreover, we extend this class of spatial covariance functions to the spatio-temporal setting using the idea used in...

Evaluating agricultural land management practices requires knowledge of soil spatial variability and understanding their relationships. Spatial distributions for fourteen soil physical and chemical properties were examined in a wheat field in Sorkhankalateh district, in Golestan province, Iran. 101 soil samples at the distances of 5m, 10m and 20m as nested grid were collected at the depth of 0-...