Spatial and Panel Data Analysis

Diffusion-enhanced spatio-temporal models for estimating spatial expansion

This paper introduces a diffusion-enhanced spatio-temporal model to quantify spatial expansion dynamics, showing it outperforms separable models in estimating expansion processes.

HiBASIL: Hierarchical Bayesian Source Inference and Localization for Spatial Epidemiology

HiBASIL accurately localizes multiple sources in spatial epidemiology, handling unbalanced foci and sparse data with high precision.

Benchmarking spatial interpolation methods for brain maps

This study benchmarks spatial interpolation methods for brain maps, finding that stochastic frameworks like Ordinary Kriging and Regression Kriging outperform deterministic methods in accuracy and biological realism.

Spatial Dependence and Heterogeneity in Molecular Imaging: Moran Quadrant Maps Enable Advanced Spatial-Statistical Analysis

The paper introduces Moran quadrant maps and workflows for spatial-statistical analysis of molecular imaging data, enabling scalable exploration of spatial dependence and heterogeneity.

The impact of heterogeneous spatial autocorrelation on comparisons of brain maps

This paper shows how heterogeneous spatial autocorrelation affects brain map comparisons and introduces a Bayesian spatial regression approach for valid statistical inference.

Tensor P-Spline Smoothing for Spatial Analysis of Plant Breeding Trials

The paper introduces a P-spline smoothing method for spatial analysis of plant breeding trials, finding that first differences are more practical than second differences for routine use.