- Referenced in 389 articles
- Univariate and Multivariate Hierarchical Point-referenced Spatial Models. Scientists and investigators in such diverse fields ... forestry, disease mapping, and economics often encounter spatially referenced data collected over a fixed ... often best analyzed with Bayesian hierarchical models. Unfortunately, fitting such models involves computationally intensive Markov ... encompassing a wide variety of Gaussian spatial process models for univariate as well as multivariate...
- Referenced in 142 articles
- spatstat: Spatial Point Pattern analysis, model-fitting, simulation, tests , A package for analysing spatial data ... exploratory data analysis, model-fitting, simulation, spatial sampling, model diagnostics, and formal inference. Data types ... include point patterns, line segment patterns, spatial windows, pixel images and tessellations. Exploratory methods include ... indices, mark dependence diagnostics etc. Point process models can be fitted to point pattern data...
- Referenced in 426 articles
- generalized linear models and nonlinear models, and time series, spatial data and point processes. Chapter...
- Referenced in 130 articles
- parallel coordinate plots; and more formal spatial data modeling that draws on the extensive Spatial...
- Referenced in 74 articles
- against dynamical spatial logic specifications. The Spatial Logic Model Checker is a tool for verifying ... expressed in the spatial logic for concurrency of Caires and Cardelli. Model-checking ... topology, it is crucial to reason about spatial properties and structural dynamics. The SLMC ... supports the combined analysis of behavioral and spatial properties of systems. The implementation, written...
- Referenced in 46 articles
- regression, nonlinear mixed-effect models, and spatial models for count data. In each case...
- Referenced in 308 articles
- random fields. Theory and applications. Researchers in spatial statistics and image analysis are familiar with ... longitudinal and survival data, spatio-temporal models, graphical models, and semi-parametric statistics. With ... such widespread use in the field of spatial statistics, it is surprising that there remains ... GMRFs in complex hierarchical models, in which statistical inference is only possible using Markov Chain...
- Referenced in 38 articles
- package spdep: Spatial dependence: weighting schemes, statistics and models , A collection of functions to create ... functions for estimating spatial simultaneous autoregressive (SAR) lag and error models, impact measures ... weighted and unweighted SAR and CAR spatial regression models, semi-parametric and Moran eigenvector spatial ... filtering, GM SAR error models, and generalized spatial two stage least squares models...
- Referenced in 96 articles
- squares for serially or spatially correlated observations, generalized linear models, and quantile regression...
- Referenced in 119 articles
- Rank Kriging is a tool for spatial/spatio-temporal modelling and prediction with large datasets. The approach ... building block of the Spatial Random Effects (SRE) model, on which this package is based...
- Referenced in 47 articles
- toolbox for fitting complex spatial point process models using integrated nested Laplace approximation (INLA). This ... toolbox for routinely fitting complex models to realistic spatial point pattern data. We consider models...
- Referenced in 32 articles
- package SpatialExtremes: Modelling Spatial Extremes. This package proposes several approaches for spatial extremes modelling...
- Referenced in 17 articles
- data analysis, geovisualization, spatial autocorrelation and spatial modeling. OpenGeoDa is the cross-platform, open source ... package was initially developed by the Spatial Analysis Laboratory of the University of Illinois ... performs basic linear regression. As for spatial models, both the spatial lag model ... spatial error model, both estimated by maximum likelihood, are included. OpenGeoDa is released under...
- Referenced in 20 articles
- provides Matlab routines to estimate spatial panel data models at his website. This article extends ... spatial panel data model contains spatial and/or time-period fixed effects, the direct and indirect ... selection framework to determine which spatial panel data model best describes the data. To demonstrate...
- Referenced in 17 articles
- geoRglm - a package for generalised linear spatial models , Functions for inference in generalised linear spatial...
- Referenced in 50 articles
- vanilla Λ cold dark matter model to include spatial curvature and a varying equation...
- Referenced in 37 articles
- Reading, writing, manipulating, analyzing and modeling of gridded spatial data. The package implements basic...
- Referenced in 68 articles
- linear programming (MINLP) models and can be solved by spatial Branch& Bound (sBB) techniques...
- Referenced in 15 articles
- package splm: Econometric Models for Spatial Panel Data. ML and GM estimation and diagnostic testing ... econometric models for spatial panel data...
- Referenced in 14 articles
- package CARBayes: Spatial Generalised Linear Mixed Models for Areal Unit Data. Implements a class ... univariate and multivariate spatial generalised linear mixed models for areal unit data, with inference ... binomial, Gaussian or Poisson. Spatial autocorrelation is modelled by a set of random effects, which ... including a multivariate CAR (MCAR) model for multivariate spatial data. Full details are given...