Sentence examples for using a spatial regression from inspiring English sources

These misspecification effects can be corrected using a spatial regression model.

Using a spatial regression discontinuity design, we exploit the within-state variation in language groups in Switzerland to provide evidence about cultural differences in LTC use.

Bowers (2013) used a spatial regression model to examine the relationship between internal theft, inside risky facilities, and external theft, outside a facility.

This process involved using all 25 components to perform a spatial regression against each separate fMRI data set and then using the resulting normalized time-course matrices to perform a temporal regression to estimate subject-specific maps that reflect the subject specific strength of functional connectivity.

Given ground data locations and coinciding LIDAR height metrics, we used a Bayesian spatial regression model (BAY) to make pixel-level biomass predictions.

Detailed illustrations of the modified predictive process using multivariate spatial regression with both a simulated and a real dataset are offered.

In a resource selection analysis using multivariable spatial regression analysis, we show that at a spatial scale of 70 m open and low cover and distance to water are important predictors of movement pathway density.

In the current analysis we report key results about comparing FIA data with two high resolution (30-m) biomass maps, one using random forest and one using Bayesian spatial regression (see Methods) at both the plot and county scales in a case study of the Anne Arundel and Howard counties in Maryland (Figure 1).

In the current analysis we report key results about comparing FIA data with two high resolution (30-m) biomass maps, one using random forest and one using Bayesian spatial regression (see Methods) at both the plot and county scales in a case study of the Anne Arundel and Howard counties in Maryland.

That is, Y i  ∼  Bern(p i ) and so we model the risk of FGM/C using a Hierarchical spatial logistic regression model that accounts for excess heterogeneity and spatial similarity between counties.

This study quantifies the spatial risk of alcohol-related pedestrian injury in New York City at the census tract level over a recent 10-year period using a Bayesian hierarchical spatial regression model with Integrated Nested Laplace approximations.