• spBayes

  • Referenced in 389 articles [sw10160]
  • encompassing a wide variety of Gaussian spatial process models for univariate as well as multivariate...
  • bootlib

  • Referenced in 461 articles [sw40642]
  • nonlinear models, and time series, spatial data and point processes. Chapter 9 describes how variance...
  • Graphs

  • Referenced in 109 articles [sw12277]
  • systems researchers investigate materialization tradeoffs, query processing on spatial networks, and reachability queries; and theoretical...
  • INLA

  • Referenced in 48 articles [sw07535]
  • toolbox for fitting complex spatial point process models using integrated nested Laplace approximation (INLA). This ... spatial point pattern data. We consider models that are based on log-Gaussian Cox processes...
  • ForceAtlas2

  • Referenced in 11 articles [sw25775]
  • ability to display the spatialization process, aiming at transforming the network into ... close to other algorithms used for network spatialization. We do not claim a theoretical advance...
  • Surveillance

  • Referenced in 35 articles [sw00932]
  • well as continuous-time processes having discrete or continuous spatial resolution...
  • LatticeKrig

  • Referenced in 8 articles [sw15594]
  • combination (e.g. an integral) of the spatial process. Included are generic methods for prediction, standard...
  • CGAL

  • Referenced in 402 articles [sw00118]
  • volume mesh generation, skin surfaces), geometry processing (surface mesh simplification, subdivision and parameterization, as well ... Support Library offers geometric object generators and spatial sorting functions, as well as a matrix...
  • spatstat

  • Referenced in 143 articles [sw04429]
  • types include point patterns, line segment patterns, spatial windows, pixel images and tessellations. Exploratory methods ... segregation indices, mark dependence diagnostics etc. Point process models can be fitted to point pattern...
  • raster

  • Referenced in 37 articles [sw08287]
  • gridded spatial data. The package implements basic and high-level functions. Processing of very large...
  • neural ideal

  • Referenced in 6 articles [sw27552]
  • study of how the brain processes spatial information. Neurons in the brain represent external stimuli...
  • npsp

  • Referenced in 5 articles [sw31433]
  • spatial trend and variogram functions (for spatial processes). Nonparametric residual kriging (spatial prediction...
  • GPvecchia

  • Referenced in 22 articles [sw41328]
  • Approximations. Fast scalable Gaussian process approximations, particularly well suited to spatial (aerial, remote-sensed...
  • spNNGP

  • Referenced in 8 articles [sw31449]
  • Datasets using Nearest Neighbor Gaussian Processes. Fits univariate Bayesian spatial regression models for large datasets...
  • KLTOOL

  • Referenced in 15 articles [sw12844]
  • small number of spatially coherent structures can be processed. A key feature of kltool...
  • convoSPAT

  • Referenced in 8 articles [sw15289]
  • convolution-based nonstationary Gaussian process models to point-referenced spatial data. The nonstationary covariance function ... specify the underlying correlation structure and which spatial dependence parameters should be allowed to vary ... over space: the anisotropy, nugget variance, and process variance. The parameters are estimated via maximum ... Also provided are functions to fit stationary spatial models for comparison, calculate the kriging predictor...
  • inlabru

  • Referenced in 5 articles [sw40209]
  • Gaussian Modelling using INLA and Extensions. Facilitates spatial and general latent Gaussian modeling using integrated ... process likelihood for modeling univariate and spatial point processes based on ecological survey data. Model...
  • SPM

  • Referenced in 9 articles [sw20505]
  • construction and assessment of spatially extended statistical processes used to test hypotheses about functional imaging...
  • laGP

  • Referenced in 28 articles [sw14043]
  • Gaussian Process Regression. Performs approximate GP regression for large computer experiments and spatial datasets...
  • GeoMLA

  • Referenced in 3 articles [sw41372]
  • often ignored in the modeling process. Spatial auto-correlation, especially if still existent ... This paper presents a random forest for spatial predictions framework (RFsp) where buffer distances from ... process. The RFsp framework is illustrated with examples that use textbook datasets and apply spatial...