4 citations · 4 across the 2 of their papers we have counts for
5 papers
Preferential Sampling for Bivariate Spatial Data
Shinichiro Shirota, Alan E. Gelfand
Preferential sampling provides a formal modeling specification to capture the effect of bias in a set of sampling locations on inference when a geostatistical model is used to expl…
Clarifying species dependence under joint species distribution modeling
Alan E. Gelfand, Shinichiro Shirota
Joint species distribution modeling is attracting increasing attention these days, acknowledging the fact that individual level modeling fails to take into account expected depende…
Conjugate Nearest Neighbor Gaussian Process Models for Efficient Statistical Interpolation of Large Spatial Data
Shinichiro Shirota, Andrew O. Finley, Bruce D. Cook +1
A key challenge in spatial statistics is the analysis for massive spatially-referenced data sets. Such analyses often proceed from Gaussian process specifications that can produce…
Preferential sampling for presence/absence data and for fusion of presence/absence data with presence-only data
Alan. E. Gelfand, Shinichiro Shirota
Presence/absence data and presence-only data are the two customary sources for learning about species distributions over a region. We illuminate the fundamental modeling difference…
Scalable Inference for Space-Time Gaussian Cox Processes
Shinichiro Shirota, Sudipto Banerjee
The log-Gaussian Cox process is a flexible and popular class of point pattern models for capturing spatial and space-time dependence for point patterns. Model fitting requires appr…