An explicit link between Gaussian fields and Gaussian Markov random fields: the stochastic partial differential equation approach
Summary Continuously indexed Gaussian fields (GFs) are the most important ingredient in
spatial statistical modelling and geostatistics. The specification through the covariance …
spatial statistical modelling and geostatistics. The specification through the covariance …
Labeled random finite sets and multi-object conjugate priors
The objective of multi-object estimation is to simultaneously estimate the number of objects
and their states from a set of observations in the presence of data association uncertainty …
and their states from a set of observations in the presence of data association uncertainty …
Determinantal point processes for machine learning
Determinantal point processes (DPPs) are elegant probabilistic models of repulsion that
arise in quantum physics and random matrix theory. In contrast to traditional structured …
arise in quantum physics and random matrix theory. In contrast to traditional structured …
Springer series in statistics
The idea for this book came from the time the authors spent at the Statistics and Applied
Mathematical Sciences Institute (SAMSI) in Research Triangle Park in North Carolina …
Mathematical Sciences Institute (SAMSI) in Research Triangle Park in North Carolina …
[图书][B] Statistical analysis and modelling of spatial point patterns
J Illian, A Penttinen, H Stoyan, D Stoyan - 2008 - books.google.com
Spatial point processes are mathematical models used to describe and analyse the
geometrical structure of patterns formed by objects that are irregularly or randomly …
geometrical structure of patterns formed by objects that are irregularly or randomly …
From multivariate to functional data analysis: Fundamentals, recent developments, and emerging areas
Functional data analysis (FDA), which is a branch of statistics on modeling infinite
dimensional random vectors resided in functional spaces, has become a major research …
dimensional random vectors resided in functional spaces, has become a major research …
inlabru: an R package for Bayesian spatial modelling from ecological survey data
FE Bachl, F Lindgren, DL Borchers… - Methods in Ecology …, 2019 - Wiley Online Library
Spatial processes are central to many ecological processes, but fitting models that
incorporate spatial correlation to data from ecological surveys is computationally …
incorporate spatial correlation to data from ecological surveys is computationally …
[图书][B] Individual-based methods in forest ecology and management
A Pommerening, P Grabarnik - 2019 - Springer
Individual-based forest ecology and management, where the focus is on individual plants in
the context of their populations, draws on a large body of different quantitative methods that …
the context of their populations, draws on a large body of different quantitative methods that …
Joint detection and estimation of multiple objects from image observations
The problem of jointly detecting multiple objects and estimating their states from image
observations is formulated in a Bayesian framework by modeling the collection of states as a …
observations is formulated in a Bayesian framework by modeling the collection of states as a …
[图书][B] Spatial statistics and modeling
C Gaetan, X Guyon - 2010 - Springer
Spatial analysis methods have seen a rapid rise in popularity due to demand from a wide
range of fields. These include, among others, biology, spatial economics, image processing …
range of fields. These include, among others, biology, spatial economics, image processing …