
FRK
 Referenced in 119 articles
[sw19172]
 naturally allows for nonstationary, anisotropic covariance functions and the use of observations with varying ... projected field is a key building block of the Spatial Random Effects (SRE) model ... based. The package FRK provides helper functions to model, fit, and predict using...

ToulBar2
 Referenced in 22 articles
[sw07289]
 Graphical Models such as Cost Function Networks, Markov Random Fields, Weighted Constraint Satisfaction Problems, Weighted...

LatticeKrig
 Referenced in 8 articles
[sw15594]
 LatticeKrig: Multiresolution Kriging Based on Markov Random Fields. Methods for the interpolation of large spatial ... functions and provides spatial estimates that are comparable to standard families of covariance functions. Using ... through compactly supported basis functions and a Markov random field model for the basis coefficients ... domain. The Markov random field approach combined with a basis function representation makes the implementation...

adapref
 Referenced in 2 articles
[sw42799]
 minimal assumptions on their functional shapes via Markov random field priors. We provide efficient algorithms...

iSNOPseAAC
 Referenced in 39 articles
[sw22446]
 transducing signals to regulate various cellular functions and signaling events. Snitrosylation ... predictor was implemented using the conditional random field (CRF) algorithm. As a demonstration, a benchmark...

constr_tt
 Referenced in 1 article
[sw13066]
 involved in highorder correlation functions of Gaussian random fields. Requires the TT toolbox. Implemented...

EFD
 Referenced in 54 articles
[sw04152]
 number of multiplications per bit as a function of the I/M ratio, i.e. the number ... provide an inversion in the ground field. In order to do this, the authors first ... combine “windows” techniques, and average over many random scalars of given size...

growfunctions
 Referenced in 2 articles
[sw16375]
 indexed functions under either of Gaussian process (GP) or intrinsic Gaussian Markov random field (iGMRF ... process mixture allows subgroupings of the functions to share the same covariance or precision...

HLM
 Referenced in 44 articles
[sw06516]
 each level, but it also predicts the random effects associated with each sampling unit ... this field, it is suitable for use with data from any research field that have ... nominal outcome variables and assumes a functional relationship between the expectation of the outcome...

spTest
 Referenced in 4 articles
[sw19766]
 second order properties of the random field. A scientist developing a model for spatial data ... spatial covariance function is isotropic. Isotropy implies that spatial dependence is a function of only ... desirable. To avoid specification of the covariance function, a number of nonparametric tests of isotropy ... spatial and spectral representations of random fields. Several of these nonparametric tests are implemented...

excursions
 Referenced in 1 article
[sw15741]
 package excursions. Functions that compute probabilistic excursion sets, contour credibility regions, contour avoiding regions ... latent Gaussian random processes and fields. The package also contains functions that calculate these quantities...

multivariance
 Referenced in 7 articles
[sw31266]
 detect and quantify dependence. The necessary functions are implemented in this packages, and examples ... KellerRessel, R.L. Schilling, Detecting independence of random vectors: generalized distance covariance and Gaussian covariance. VMSTA ... measures for random vectors. . G. Berschneider, B. Böttcher, On complex Gaussian random fields, Gaussian quadratic...

cgeostat
 Referenced in 3 articles
[sw23163]
 cgeostat Software for Analyzing ComplexValued Random Fields. Given a vectorial data ... environmental sciences and meteorology (e.g., for wind fields). In such a case, some computational difficulties ... estimating and modeling a complex covariance function, for predicting complex variables as well ... geostatistical analysis of complexvalued random fields is presented and an application is demonstrated...

COLOSSUS
 Referenced in 1 article
[sw38823]
 function. The LSS module is concerned with the properties of peaks in Gaussian random fields ... height, peak curvature, halo bias, and mass function. The halo module deals with spherical overdensity...

LSD
 Referenced in 9 articles
[sw14340]
 role in many diverse scientific and engineering fields. However, it is well known that ... distributions, such as density and distribution functions, random numbers, parameters estimate, and goodness of data...

GiRaF
 Referenced in 2 articles
[sw41649]
 calculation on, and sampling from Gibbs Random Fields, and more precisely general homogeneous Potts model ... small rectangular lattices. Beside the latter function, it contains method that give exact sample from...

glmie
 Referenced in 2 articles
[sw13249]
 estimation toolbox. The glmie toolbox contains functionality for estimation and inference in generalised linear ... connected undirected graphical models or Markov random fields with Gaussian and nonGaussian potentials ... provide a wide choice of penalty functions for estimation, potential functions for inference and matrix...

Smash
 Referenced in 2 articles
[sw15447]
 matrix groups defined over finite fields. These functions permit the user to construct certain types ... normal subgroup; and to select random elements with certain properties. The code was developed ... categories of matrix groups defined over finite fields...

MCdevelop
 Referenced in 5 articles
[sw09208]
 range of functionality in the SS software needed for advanced precision quantum field theory calculations ... involve independent generation of large sets of random “events”, often requiring considerable CPU power. Since ... sophisticated framework featuring all the above mentioned functionality has been implemented. MCdevelop represents its latest...

zkSNARK
 Referenced in 13 articles
[sw22495]
 terms of space complexity as a function of the size of the computation being proved ... methods for exploiting the proof systems’ field structure and nondeterminism, we achieve the first ... proof composition. Our zkSNARK implementation runs randomaccess machine programs and produces proofs...