properties of clusters using interactive neighbourhood graphs.
By clicking on the node representing the cluster, information
about the cluster is provided using additional graphics or
summary statistics. For microarray data, tables with links to
genetic databases like gene ontolgy can be created for each
Packaged: Wed May 6 17:23:33 2009; scharl

genetic databases like NCBI Entrez Gene can be created for each

Depends: R (>= 2.10), graphics, methods, flexclust (>= 1.0-0),

Description: R application programming interface (API) for Deep Forest which based on Zhou and Feng (2017).
Deep Forest: Towards an Alternative to Deep Neural Networks. (<arXiv:1702.08835v2>) or Zhou and Feng (2017).
Deep Forest. (<arXiv:1702.08835>). And for the Python module 'gcForest' (<https://github.com/pylablanche/gcForest>).

Title: Analyze and Interpolate Geostatistical Count Data using Gaussian
Description: Provides a variety of functions to analyze and model
geostatistical count data with Gaussian copulas, including
2) correlation structure assessment (here also known as the NORTA);
3) calculate multivariate normal rectangle probabilities;
4) likelihood inference and parallel prediction at unsampled locations.
Suggests: EQL, FNN, gcmr, lattice, latticeExtra, Matrix, MASS,

Suggests: EQL, FNN, lattice, latticeExtra, Matrix, MASS, numDeriv,

Title: Analysis of Geostatistical Count Data using Gaussian Copulas
2) correlation structure assessment (here also known as the Normal To Anything);
4) likelihood inference and parallel prediction at predictive locations.

Description of the method is available from: Han and DeOliveira (2018) <doi:10.18637/jss.v087.i13>.

Suggests: EQL, FNN, gcmr, lattice, latticeExtra, mvtnorm, Matrix, MASS,

Suggests: EQL, FNN, lattice, latticeExtra, mvtnorm, Matrix, MASS,

Title: Generalized Coupled Tensor Factorization
Description: Multiple matrices/tensors can be specified and decomposed simultaneously by Probabilistic Latent Tensor Factorisation (PLTF). See the reference section of GitHub README.md <https://github.com/rikenbit/gcTensor>, for details of the method.