Introduces conditional autoregressive models for spatially dependent functional data with consistent covariance estimation via conditional centering and superconsistent, asymptotically normal estimation of the spatial dependence parameter under an expanding lattice.
Biometrika , volume=
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
JASPER is a new joint Bayesian regression model for spatial transcriptomics that accounts for correlations between genes to better identify spatially varying genes.
citing papers explorer
-
A new class of functional conditional autoregressive models
Introduces conditional autoregressive models for spatially dependent functional data with consistent covariance estimation via conditional centering and superconsistent, asymptotically normal estimation of the spatial dependence parameter under an expanding lattice.
-
JASPER: Joint Bayesian Analysis of Spatial Expression via Regression
JASPER is a new joint Bayesian regression model for spatial transcriptomics that accounts for correlations between genes to better identify spatially varying genes.