• fields

  • Referenced in 56 articles [sw08187]
  • with an emphasis on splines, spatial data and spatial statistics. The major methods include cubic ... splines, Kriging and compact covariances for large data sets. The splines and Kriging methods ... functions for plotting and working with spatial data as images. This package also contains ... implementation of sparse matrix methods for large spatial data sets and currently requires the sparse...
  • raster

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

  • Referenced in 119 articles [sw19172]
  • tool for spatial/spatio-temporal modelling and prediction with large datasets. The approach, discussed in Cressie ... typically much smaller than the number of data points (or polygons) m. The method naturally ... building block of the Spatial Random Effects (SRE) model, on which this package is based...
  • INLA

  • Referenced in 47 articles [sw07535]
  • fitting complex models to realistic spatial point pattern data. We consider models that are based ... fitted to two rather different examples, a large rainforest data set with covariates...
  • BayesNSGP

  • Referenced in 3 articles [sw30769]
  • process inference to account for very large spatial data sets (Finley, et al (2017) ). Bayesian...
  • spTimer

  • Referenced in 18 articles [sw24237]
  • Modelling. Fits, spatially predicts and temporally forecasts large amounts of space-time data using...
  • 3DGIS

  • Referenced in 2 articles [sw03311]
  • objects in 3DGIS. Adaptive rendering large and complex spatial data has become an important research ... data to the client efficiently, this paper proposes a node-layer data model ... manage the 3D scene. Because the large spatial data and limited network bandwidth...
  • MRST-co2lab

  • Referenced in 6 articles [sw25312]
  • storage is characterized by scarce data, large spans in spatial and temporal scales, and delicate...
  • AUTOCLUST+

  • Referenced in 4 articles [sw02259]
  • Argument free clustering for large spatial point-data sets via boundary extraction from Delaunay Diagram...
  • 2DECOMP

  • Referenced in 26 articles [sw12729]
  • software framework in Fortran to build large-scale parallel applications. It is designed for applications ... using three-dimensional structured mesh and spatially implicit numerical algorithms. At the foundation it implements ... general-purpose 2D pencil decomposition for data distribution on distributed-memory platforms...
  • BrainWeb

  • Referenced in 48 articles [sw16790]
  • complicated due to the lack of reference data (”ground truth”). Also, optimal selection ... imaging parameters is difficult due to the large parameter space. BrainWeb makes available ... from a fuzzy digital phantom containing the spatial...
  • ParBreZo

  • Referenced in 7 articles [sw08731]
  • Topographic data are increasingly available at high resolutions (<10 m) over large spatial extents ... presented, and the Single Process Multiple Data (SPMD) paradigm of distributed-memory parallelism is implemented...
  • RAMSES

  • Referenced in 41 articles [sw18064]
  • structure formation in the universe with high spatial resolution. The code is based on Adaptive ... Refinement (AMR) technique, with a tree-based data structure allowing recursive grid refinements ... negligible. Results obtained in a large N-body and hydrodynamical simulation of structure formation...
  • Spatial Statistics

  • Referenced in 8 articles [sw06026]
  • Spatial Statistics Software and Spatial Data. The public domain Spatial Statistics Toolbox for Matlab ... large-scale lattice models. The Matlab Spatial Statistics Toolbox includes code for simultaneous spatial autoregressions ... conditional spatial autoregressions (CAR), and mixed regressive spatially autoregressive (MRSA) models. In addition, it contains ... Matlab Spatial Statistics Toolbox includes the most common estimators employed in spatial econometrics. These products...
  • ScanComplete

  • Referenced in 3 articles [sw36658]
  • Scans. We introduce ScanComplete, a novel data-driven approach for taking an incomplete 3D scan ... handle large scenes with varying spatial extent, managing the cubic growth in data size ... scene subvolumes but deployed on arbitrarily large scenes at test time. In addition, we propose...
  • ProbitSpatial

  • Referenced in 3 articles [sw37939]
  • available and voluminous geospatial and location data, older estimation techniques cannot withstand the course ... fast and accurate estimations of Spatial Autoregressive and Spatial Error Models under Probit specification. They ... spatial weight matrix is in convenient sparse form, as is typically the case of large ... produce fast computations for large sparse matrixes. Possible applications of spatial binary choice models include...
  • SamplingBigData

  • Referenced in 1 article [sw31430]
  • probability samples using large data sets. This includes spatially balanced sampling in multi-dimensional spaces...
  • SLOM

  • Referenced in 7 articles [sw36331]
  • SLOM, we are able to discern local spatial outliers that are usually missed by global ... data point and suppresses the reporting of outliers in highly unstable areas, where data ... real data sets that show that our approach is novel and scalable to large datasets...
  • pyunicorn

  • Referenced in 8 articles [sw19314]
  • structure of statistical interrelationships in large data sets of time series and, subsequently, investigating this ... theory such as measures and models for spatial networks, networks of interacting networks, node-weighted...
  • TBSIM

  • Referenced in 19 articles [sw21202]
  • turning bands method. The simulation of spatially correlated Gaussian random fields is widespread in geologic ... conditioning these realizations to a set of data and (iii) back-transforming the Gaussian values ... Such programs can deal with simulations over large domains and handle anisotropic and nested covariance...