6 papers · 1 filter
Decorated graphons for temporal network estimation
Charles Dufour, Sofia C. Olhede
We propose a unified nonparametric framework for modeling time-evolving networks using decorated graphons (also known as probability-graphons): symmetric functions that assign to e…
The partial K function
Jake P. Grainger, Tuomas A. Rajala, David J. Murrell +1
The K function and its related statistics have been an enduring tool in the analysis of spatial point processes, providing an easy to compute and interpret summary statistic for ch…
Irregularly and incompletely sampled random fields in the Earth sciences: Analysis and synthesis of parameterized covariance models
Olivia L. Walbert, Frederik J. Simons, Arthur P. Guillaumin +1
We study how sampling geometry contributes to uncertainty in modeling spatial geophysical observations as sampled random fields characterized by stationary, isotropic, parametric c…
Maximum-likelihood estimation of the Matérn covariance structure of isotropic spatial random fields on finite, sampled grids
Frederik J. Simons, Olivia L. Walbert, Arthur P. Guillaumin +3
We present a statistically and computationally efficient spectral-domain maximum-likelihood procedure to solve for the structure of Gaussian spatial random fields within the Matern…
Spectral estimation for spatial point processes and random fields
Jake P. Grainger, Tuomas A. Rajala, David J. Murrell +1
Spatial variables can be observed in many different forms, such as regularly sampled random fields (lattice data), point processes, and randomly sampled spatial processes. Joint an…
Graphon estimation beyond binary edges: inference for decorated graphs with applications to multiplex and weighted networks
Charles Dufour, Sofia C. Olhede
We introduce the first doubly non-parametric estimation method for decorated graphons, a generalisation of graphons that encodes edge weights, edge types, and other edge-level attr…