The belief that relationships between explanatory variables and a response variable in a regression model may vary within a study area has lead to the development of Bayesian regression models that allow for spatially varying coefficients (Gelfand et al., 2003). In the typical application of these spatially varying coefficient process (SVCP) models, marginal inference on the spatial pattern of ...

The development of normal patterns along the primary and secondary vertebrate axes depends on the regularity of early Hox gene expression. During initial stages, these expression events form a sequential pattern of partially overlapping domains along the anteroposterior axis in coincidence with the 3' to 5' order of the genes in the Hox cluster (spatial collinearity). In addition, the genes are...

The aim of this research was to assess the possibility of conducting an absolute orientation procedure for video imagery, in which the external orientation for the first image was typical for aerial photogrammetry whereas the external orientation of the second was typical for terrestrial photogrammetry. Starting from the collinearity equations, assuming that the camera tilt angle is equal to 90...

According to the principle of space intersection、collinearity equations and error propagation law, mathematical models of theoretical accuracy of direct georeferencing are proposed in this paper. The validity and feasibility of the mathematical models are tested using four sets of actual photos at different scales and terrains. Results indicate that accuracy of direct georeferencing based on sp...

Background: Hox gene collinearity relates the sequential location of Hox genes in the 3’ to 5’ direction on the chromosome with the linear arrangement of the body elements along the anterior-posterior (A/P) axis of bilaterian embryos. This spatial Hox gene collinearity has been almost universally respected in diverse organisms like worms, insects or vertebrates. It is therefore surprising that ...

Once they have learnt about the effects of collinearity on output multiple regression models, researchers may unduly worry these and resort to (sometimes dubious) modelling techniques mitigate them. I argue that, extent that problems occur in presence collinearity, are not caused by it but rather common mental shortcuts take when interpreting statistical models can also lead them astray absence...

In this paper we address the statistics of second-order relations of feature vectors derived from image sequences. We compute the individual vector components corresponding to the visual modalities orientation, contrast transition, optic flow, and colour by conventional low-level early vision algorithms. As a main result, we observe that collinear (or parallel) line pairs are, with very great l...