In particular, the problem of testing for the existence of spatial association between two georeferenced variables is relevant for posterior modeling and inference. One evident application in this context is the quantification of the spatial correlation between two images (processes defined on a ...
Large-scale cross-sectional studies have found statistical differences among languages that pattern with environmental variables such as topography or population size. However, these studies are correlational in nature, revealing little about the possible mechanisms driving these cultural evolutionary processes...
plex gain of the l-th path between transmit antenna i and re- ceive antenna j. The α ij (l) ∼ CN 0, σ 2 l are modelled as zero mean, circularly symmetric complex Gaussian random variables with variance σ 2 l . The time delay τ l and the vari- ance σ 2 l are the same...
Variables may also be defined to create a smooth surface through the use of bivariate splines on the Cartesian coordinates of the units, for example. Spatial correlation that is due to, or well approximated by, such covariate relationships will be accounted for by their inclusion. As covariates ...
****P < 0.0001. Comparison between the clinical variables and all markers model: ***P = 0.0001. Comparison between the cell frequency and lineage marker model: *P = 0.0321.f, Accuracy of clinical progression prediction in patients with stage I LUAD; discovery cohort (n = ...
The first and second variable representing the migration history enter the model separately, mainly because there is a highly significant correlation between these two variables (correlation coefficient = 0.8, p < 0.001). In fact, the second variable is a refinement of the first one, ...
Secondly, our empirical results demonstrate the existence of significant spatial effects among neighboring regions, suggesting that spa- tial correlation should be fully considered in the study of inter-regional healthcare markets within a country. Finally, we added healthcare policy variables to the ...
Regression analysis is a statistical analysis method to determine the quantitative relationship between two or more variables. Regression analysis can be divided into linear regression analysis and nonlinear regression analysis according to the relationship type between independent variables and dependent variabl...
Spatial autocorrelation is a special case of correlation, which is the global concept that two attribute variables X and Y have some average degree of alignment between the relative magnitudes of their respective values. With correlation, for a positive alignment, large values of X tend to align ...
(PCT_ASN) on the horizontal axis. Both variables are standardized. Again, the distribution is shown in four quadrants to indicate positive and negative spatial autocorrelation. The slope of the regression line shows the degree of spatial association between the variables at neighboring locations. ...